subject:(Back Propagation)

Louisiana State University

1. Swargam, Nagajyothi. Development of a neural network approach for the assessment of the performance of traffic sign retroreflectivity.

Degree: MSCE, Civil and Environmental Engineering, 2004, Louisiana State University

URL: etd-11122004-071142 ; https://digitalcommons.lsu.edu/gradschool_theses/440

► The goal of the research was to develop a new predictive tool for assessing the performance of traffic sign retroreflectivity and to compare the developed… (more)

▼ The goal of the research was to develop a new predictive tool for assessing the performance of traffic sign retroreflectivity and to compare the developed tool with the existing linear regression models. Retroreflectivity decreases as sign sheeting ages. Currently Louisiana Department of Transportation and Development (LADOTD) replace signs with low reflectivity based on driver complaints. This practice might have resulted in premature sign replacement (removal of signs with several years of in-service life still remaining) or in non-replacement of signs that are not in compliance with LADOTD minimum reflectivity standards. In this study, both neural network models and regression models were developed to predict reflectivity of Engineering and High Intensity Grade signs. The LADOTD traffic sign inventory data of Ascension Parish traffic signs were used for model development, validation and comparison. The performance of the developed neural network models (NN models) was compared to the developed regression models (R2 models) and also to the existing retroreflectivity regression models (R1 models) developed by Wolshon et al. The R1 models were developed for traffic signs placed along Interstate and State Highway routes in the districts of New Orleans, Baton Rouge, Lafayette, and Shreveport. Also, the usability of the neural network models developed in the study was analyzed based on the data collected by Wolshon et al to develop the linear regression R1 models. The results of this study demonstrated the feasibility of using ANNs in predicting the retroreflectivity of Type I and Type III sign sheeting. The independent variables found to be statistically significant variables in explaining the performance of traffic signs retroreflectivity included age of the sign, sheeting type, and background color of sign sheeting. A comparison of the models developed with two different specifications involving different sets of independent variables showed that the models including all the variables (i.e., Age, Edge of Pavement Distance, Sign Orientation, Sign Background Color, and Sheeting Type) increased the explanatory power of the models by little. However, it was recommended to use of all deterioration variables whose effects are not non-existent.

Subjects/Keywords: back propagation

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APA (6^th Edition):

Swargam, N. (2004). Development of a neural network approach for the assessment of the performance of traffic sign retroreflectivity. (Masters Thesis). Louisiana State University. Retrieved from etd-11122004-071142 ; https://digitalcommons.lsu.edu/gradschool_theses/440

Chicago Manual of Style (16^th Edition):

Swargam, Nagajyothi. “Development of a neural network approach for the assessment of the performance of traffic sign retroreflectivity.” 2004. Masters Thesis, Louisiana State University. Accessed March 07, 2021. etd-11122004-071142 ; https://digitalcommons.lsu.edu/gradschool_theses/440.

MLA Handbook (7^th Edition):

Swargam, Nagajyothi. “Development of a neural network approach for the assessment of the performance of traffic sign retroreflectivity.” 2004. Web. 07 Mar 2021.

Vancouver:

Swargam N. Development of a neural network approach for the assessment of the performance of traffic sign retroreflectivity. [Internet] [Masters thesis]. Louisiana State University; 2004. [cited 2021 Mar 07]. Available from: etd-11122004-071142 ; https://digitalcommons.lsu.edu/gradschool_theses/440.

Council of Science Editors:

Swargam N. Development of a neural network approach for the assessment of the performance of traffic sign retroreflectivity. [Masters Thesis]. Louisiana State University; 2004. Available from: etd-11122004-071142 ; https://digitalcommons.lsu.edu/gradschool_theses/440

Vilnius Pedagogical University

2. Sargelis, Kęstas. Klaidos skleidimo atgal algoritmo tyrimai.

Degree: Master, Informatics, 2009, Vilnius Pedagogical University

URL: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090630_094557-88383 ;

►

Šiame darbe detaliai išanalizuotas klaidos skleidimo atgal algoritmas, atlikti tyrimai. Išsamiai analizuota neuroninių tinklų teorija. Algoritmui taikyti ir analizuoti sistemoje Visual Studio Web Developer 2008… (more)

Subjects/Keywords: Klaida; Sklidimas; Algoritmas; Back-propagation; Algorithm; Error

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APA (6^th Edition):

Sargelis, Kęstas. (2009). Klaidos skleidimo atgal algoritmo tyrimai. (Masters Thesis). Vilnius Pedagogical University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090630_094557-88383 ;

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

Sargelis, Kęstas. “Klaidos skleidimo atgal algoritmo tyrimai.” 2009. Masters Thesis, Vilnius Pedagogical University. Accessed March 07, 2021. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090630_094557-88383 ;.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

Sargelis, Kęstas. “Klaidos skleidimo atgal algoritmo tyrimai.” 2009. Web. 07 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Sargelis, Kęstas. Klaidos skleidimo atgal algoritmo tyrimai. [Internet] [Masters thesis]. Vilnius Pedagogical University; 2009. [cited 2021 Mar 07]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090630_094557-88383 ;.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Sargelis, Kęstas. Klaidos skleidimo atgal algoritmo tyrimai. [Masters Thesis]. Vilnius Pedagogical University; 2009. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090630_094557-88383 ;

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Brno University of Technology

3. Doupovec, Zdeněk. Rozpoznávání číslic pomocí neuronové sítě: Neural Network Number Recognition.

Degree: 2018, Brno University of Technology

URL: http://hdl.handle.net/11012/54450

► This work describes the basic concepts and principles in the field of neural networks. Closer then deals with the problem of multilayer perceptron networks, namely… (more)

Subjects/Keywords: Neuron; neuronová síť; perceptron; back-propagation; rozpoznávání číslic; učení; rozpoznávání.; Neuron; neural network; perceptron; back-propagation; number recognition; learning; recognition.

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APA (6^th Edition):

Doupovec, Z. (2018). Rozpoznávání číslic pomocí neuronové sítě: Neural Network Number Recognition. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/54450

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Doupovec, Zdeněk. “Rozpoznávání číslic pomocí neuronové sítě: Neural Network Number Recognition.” 2018. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/54450.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Doupovec, Zdeněk. “Rozpoznávání číslic pomocí neuronové sítě: Neural Network Number Recognition.” 2018. Web. 07 Mar 2021.

Vancouver:

Doupovec Z. Rozpoznávání číslic pomocí neuronové sítě: Neural Network Number Recognition. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/54450.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Doupovec Z. Rozpoznávání číslic pomocí neuronové sítě: Neural Network Number Recognition. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/54450

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Brno University of Technology

4. Borkovec, Tomáš. Neuronové sítě v kryptografii: Neural networks in cryptography.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/28187

► Bachelor's thesis aims to introduce neural networks and their properties, which can be used for creating cryptographic protocols based on neural networks. It proposed concrete… (more)

Subjects/Keywords: Neuronové sítě; back-propagation; kryptografie; neuronové sítě v kryptografii; hašovací funkce; Neural network; back – propagation; cryptography; neural cryptography; hash function

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APA (6^th Edition):

Borkovec, T. (2019). Neuronové sítě v kryptografii: Neural networks in cryptography. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/28187

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Borkovec, Tomáš. “Neuronové sítě v kryptografii: Neural networks in cryptography.” 2019. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/28187.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Borkovec, Tomáš. “Neuronové sítě v kryptografii: Neural networks in cryptography.” 2019. Web. 07 Mar 2021.

Vancouver:

Borkovec T. Neuronové sítě v kryptografii: Neural networks in cryptography. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/28187.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Borkovec T. Neuronové sítě v kryptografii: Neural networks in cryptography. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/28187

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Brno University of Technology

5. Lavický, Vojtěch. Využití umělé inteligence v kryptografii: The use of artificial intelligence in cryptography.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/11105

► Goal of this thesis is to get familiar with problematics of neural networks and commonly used security protocols in cryptography. Theoretical part of the thesis… (more)

Subjects/Keywords: neuron; perceptron; neuronová síť; Back-propagation; kryptografie; MATLAB; SIMULINK; neuron; perceptron; neural network; Back-propagation; cryptography; MATLAB; SIMULINK

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APA (6^th Edition):

Lavický, V. (2019). Využití umělé inteligence v kryptografii: The use of artificial intelligence in cryptography. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/11105

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lavický, Vojtěch. “Využití umělé inteligence v kryptografii: The use of artificial intelligence in cryptography.” 2019. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/11105.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lavický, Vojtěch. “Využití umělé inteligence v kryptografii: The use of artificial intelligence in cryptography.” 2019. Web. 07 Mar 2021.

Vancouver:

Lavický V. Využití umělé inteligence v kryptografii: The use of artificial intelligence in cryptography. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/11105.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lavický V. Využití umělé inteligence v kryptografii: The use of artificial intelligence in cryptography. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/11105

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Brno University of Technology

6. Kaňa, Ondřej. Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms.

Degree: 2014, Brno University of Technology

URL: http://hdl.handle.net/11012/11106

► Digital watermarking is a technique for digital multimedia copyright protection. The robustness and the imperceptibility are the main requirements of the watermark. This thesis deals… (more)

Subjects/Keywords: vodoznačení; vodoznak; neuronová síť; Back-propagation; psychoakustický model; dct; watermarking; watermark; neural network; Back-propagation; psychoacoustic model; dct

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kaňa, O. (2014). Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/11106

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Kaňa, Ondřej. “Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms.” 2014. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/11106.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Kaňa, Ondřej. “Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms.” 2014. Web. 07 Mar 2021.

Vancouver:

Kaňa O. Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms. [Internet] [Thesis]. Brno University of Technology; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/11106.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kaňa O. Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms. [Thesis]. Brno University of Technology; 2014. Available from: http://hdl.handle.net/11012/11106

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Brno University of Technology

7. Čermák, Justin. Implementace neuronové sítě do mikrokontroléru: Neural network implementation into microcontroler.

Degree: 2018, Brno University of Technology

URL: http://hdl.handle.net/11012/1045

► This bachelor thesis handles about implementation of multi layer neural networks for character recognition into the PC and microcontrollers. The practical part describes how to… (more)

Subjects/Keywords: umělá neuronová síť; mikrokontrolér; perceptron; error back propagation; rozpoznávání znaků; artificial neural network; microcontroller; perceptron; error back propagation; character recognition

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APA (6^th Edition):

Čermák, J. (2018). Implementace neuronové sítě do mikrokontroléru: Neural network implementation into microcontroler. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/1045

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Čermák, Justin. “Implementace neuronové sítě do mikrokontroléru: Neural network implementation into microcontroler.” 2018. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/1045.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Čermák, Justin. “Implementace neuronové sítě do mikrokontroléru: Neural network implementation into microcontroler.” 2018. Web. 07 Mar 2021.

Vancouver:

Čermák J. Implementace neuronové sítě do mikrokontroléru: Neural network implementation into microcontroler. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/1045.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Čermák J. Implementace neuronové sítě do mikrokontroléru: Neural network implementation into microcontroler. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/1045

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Brno University of Technology

8. Kaňa, Ondřej. Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/20969

► Digital watermarking is a technique for digital multimedia copyright protection. The robustness and the imperceptibility are the main requirements of the watermark. This thesis deals… (more)

Subjects/Keywords: vodoznačení; vodoznak; neuronová síť; Back-propagation; psychoakustický model; dct; watermarking; watermark; neural network; Back-propagation; psychoacoustic model; dct

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kaňa, O. (2019). Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/20969

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Kaňa, Ondřej. “Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms.” 2019. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/20969.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Kaňa, Ondřej. “Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms.” 2019. Web. 07 Mar 2021.

Vancouver:

Kaňa O. Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/20969.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kaňa O. Neuronové sítě v algoritmech vodoznačení audio signálů: Neural networks in audio signal watermarking algorithms. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/20969

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

9. Tsai, Ying-Wei. Performance Evaluation of Identification Methods for the Stress Calls of Squirrelfishesï¼Pisces:Holocentridaeï¼.

Degree: Master, Undersea Technology, 2008, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0125108-162908

► In the study of sound identification, land animals such as birds and bats have been well investigated, and so are their habitats. On the other… (more)

Subjects/Keywords: Stepwise Discriminant; Analysis of Variance; Kolmogorov-Smirnov Test; Holocendridae; Back-propagation

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APA (6^th Edition):

Tsai, Y. (2008). Performance Evaluation of Identification Methods for the Stress Calls of Squirrelfishesï¼Pisces:Holocentridaeï¼. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0125108-162908

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Tsai, Ying-Wei. “Performance Evaluation of Identification Methods for the Stress Calls of Squirrelfishesï¼Pisces:Holocentridaeï¼.” 2008. Thesis, NSYSU. Accessed March 07, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0125108-162908.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Tsai, Ying-Wei. “Performance Evaluation of Identification Methods for the Stress Calls of Squirrelfishesï¼Pisces:Holocentridaeï¼.” 2008. Web. 07 Mar 2021.

Vancouver:

Tsai Y. Performance Evaluation of Identification Methods for the Stress Calls of Squirrelfishesï¼Pisces:Holocentridaeï¼. [Internet] [Thesis]. NSYSU; 2008. [cited 2021 Mar 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0125108-162908.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tsai Y. Performance Evaluation of Identification Methods for the Stress Calls of Squirrelfishesï¼Pisces:Holocentridaeï¼. [Thesis]. NSYSU; 2008. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0125108-162908

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Rochester Institute of Technology

10. Wehry, Stephen. Monte Carlo comparison of back-propagation, conjugate-gradient, and finite-difference training algorithms for multilayer perceptrons.

Degree: School of Mathematical Sciences (COS), 2011, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/223

► Monte Carlo Simulation is used to compare the performance of the Back-Propagation, Conjugate-Gradient, and Finite-Difference algorithms when training simple Multilayer Perceptron networks to solve pattern… (more)

Subjects/Keywords: Back-propagation; Conjugate-gradient; Monte Carlo; Neural network; Training algorithm

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wehry, S. (2011). Monte Carlo comparison of back-propagation, conjugate-gradient, and finite-difference training algorithms for multilayer perceptrons. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/223

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wehry, Stephen. “Monte Carlo comparison of back-propagation, conjugate-gradient, and finite-difference training algorithms for multilayer perceptrons.” 2011. Thesis, Rochester Institute of Technology. Accessed March 07, 2021. https://scholarworks.rit.edu/theses/223.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wehry, Stephen. “Monte Carlo comparison of back-propagation, conjugate-gradient, and finite-difference training algorithms for multilayer perceptrons.” 2011. Web. 07 Mar 2021.

Vancouver:

Wehry S. Monte Carlo comparison of back-propagation, conjugate-gradient, and finite-difference training algorithms for multilayer perceptrons. [Internet] [Thesis]. Rochester Institute of Technology; 2011. [cited 2021 Mar 07]. Available from: https://scholarworks.rit.edu/theses/223.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wehry S. Monte Carlo comparison of back-propagation, conjugate-gradient, and finite-difference training algorithms for multilayer perceptrons. [Thesis]. Rochester Institute of Technology; 2011. Available from: https://scholarworks.rit.edu/theses/223

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Georgia Tech

11. Ramachandran, Adithya. HEV fuel optimization using interval back propagation based dynamic programming.

Degree: MS, Mechanical Engineering, 2016, Georgia Tech

URL: http://hdl.handle.net/1853/55054

► In this thesis, the primary powertrain components of a power split hybrid electric vehicle are modeled. In particular, the dynamic model of the energy storage… (more)

Subjects/Keywords: HEV; Dynamic programming; Interval back propagation; Optimization; Convexity; Real time implementation

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APA (6^th Edition):

Ramachandran, A. (2016). HEV fuel optimization using interval back propagation based dynamic programming. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55054

Chicago Manual of Style (16^th Edition):

Ramachandran, Adithya. “HEV fuel optimization using interval back propagation based dynamic programming.” 2016. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/55054.

MLA Handbook (7^th Edition):

Ramachandran, Adithya. “HEV fuel optimization using interval back propagation based dynamic programming.” 2016. Web. 07 Mar 2021.

Vancouver:

Ramachandran A. HEV fuel optimization using interval back propagation based dynamic programming. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/55054.

Council of Science Editors:

Ramachandran A. HEV fuel optimization using interval back propagation based dynamic programming. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55054

Brno University of Technology

12. Sulaiman, David. Počítačem řízený hráč hry Blokus založený na metodách umělé inteligence: Artificial Intelligence-Based Player for "Blokus" Game.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/54382

► This thesis compares forward neural networks with algorithms using game theory on basis of board game Blokus. The theoretical introduction part describes the characteristics of… (more)

Subjects/Keywords: Blokus; teorie her; zpětná indukce; perceptron; neuronová síť; back propagation; Java; Swing; Blokus game; game theory; backward induction; perceptron; neural network; back propagation; Java; Swing

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APA (6^th Edition):

Sulaiman, D. (2019). Počítačem řízený hráč hry Blokus založený na metodách umělé inteligence: Artificial Intelligence-Based Player for "Blokus" Game. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/54382

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sulaiman, David. “Počítačem řízený hráč hry Blokus založený na metodách umělé inteligence: Artificial Intelligence-Based Player for "Blokus" Game.” 2019. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/54382.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sulaiman, David. “Počítačem řízený hráč hry Blokus založený na metodách umělé inteligence: Artificial Intelligence-Based Player for "Blokus" Game.” 2019. Web. 07 Mar 2021.

Vancouver:

Sulaiman D. Počítačem řízený hráč hry Blokus založený na metodách umělé inteligence: Artificial Intelligence-Based Player for "Blokus" Game. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/54382.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sulaiman D. Počítačem řízený hráč hry Blokus založený na metodách umělé inteligence: Artificial Intelligence-Based Player for "Blokus" Game. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/54382

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Brno University of Technology

13. Nagyová, Lenka. Aplikace neuronových sítí ve zpracování obrazu: Application of neural net in image processing.

Degree: 2014, Brno University of Technology

URL: http://hdl.handle.net/11012/31534

► This work focuses on the theory of artificial neural networks: the history, individual ways of learning and architecture of networks. It is also necessary to… (more)

Subjects/Keywords: Umělé neuronové sítě; zpracování obrazu; identifikace objektů; back propagation; rozpoznávání znaků; OpenCV; C/C++; Artificial neural networks; image processing; objects identification; back propagation; character recognition; OpenCV; C/C++

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Nagyová, L. (2014). Aplikace neuronových sítí ve zpracování obrazu: Application of neural net in image processing. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/31534

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nagyová, Lenka. “Aplikace neuronových sítí ve zpracování obrazu: Application of neural net in image processing.” 2014. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/31534.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nagyová, Lenka. “Aplikace neuronových sítí ve zpracování obrazu: Application of neural net in image processing.” 2014. Web. 07 Mar 2021.

Vancouver:

Nagyová L. Aplikace neuronových sítí ve zpracování obrazu: Application of neural net in image processing. [Internet] [Thesis]. Brno University of Technology; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/31534.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nagyová L. Aplikace neuronových sítí ve zpracování obrazu: Application of neural net in image processing. [Thesis]. Brno University of Technology; 2014. Available from: http://hdl.handle.net/11012/31534

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

14. Xu, Deng-Xiang. Analysis of Nitrosamine formation from Pharmaceuticals and Personal Care Products during two-stage chlorination using Back-Propagation Neural Network.

Degree: Master, Environmental Engineering, 2016, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0701116-115902

► Pharmaceuticals and personal care products (PPCPs), which are commonly abused in human activities and less effectively treated by conventional wastewater treatment technologies, are often found… (more)

▼ Pharmaceuticals and personal care products (PPCPs), which are commonly abused in human activities and less effectively treated by conventional wastewater treatment technologies, are often found in aquatic environments worldwide. PPCPs are known to form nitrogenous disinfection byproducts such as n-nitrosodimethylamine (NDMA) in nitrosamines during disinfection. Due to high carcinogenicity, nitrosamines are of wide concern in the research and practical management fields. The well-known NDMA precursors include secondary and tertiary amines, urea-based herbicide, PPCPs, amine-containing polymers, and natural organic matter (NOM). Free chlorine and ozone are two oxidants widely used during peroxidation or post-disinfection. Different levels of NDMA pollution may result by reactions of oxidant and potential precursors, as the reactions were typically simulated by laboratory experiments and explained by multiple linear or non-linear regressions or empirical models. The objective of this study was to investigate the NDMA formation from four PPCPs including ranitidine, nizatidine, chlorpheniramine, and doxylamine during two-stage chlorination, as the NDMA formation was analyzed and predicted by using the back-propagation neural network First, lab-scale two-stage chlorination experiments were conducted to study the effects of coagulation and sedimentation, peroxidation dosage, presence of inorganic nitrogen, namely nitrite, nitrate and ammonia, on NDMA formation from PPCPs. Next, the results from the early studies that discussed the optimal strategy of coagulation to remove turbidity and the formation of NDMA from herbicides in drinking water treatment processes were employed to establish and assess the applicability of the back-propagation neural network theory. Finally, the results of the two-stage chlorination simulation were analyzed by the back-propagation neural network theory, as the model was used to predict the scenarios not covered by the lab experiments. The effect of coagulation and sedimentation on the NDMA formation from PPCPs was negligible. The NDMA formation in the two-stage chlorination simulation was lower than those in the one-stage chlorination simulation, showing the effect of preoxidation. For the effect of molar ratio of total chlorine to PPCPs concentrations, the NDMA formation was significantly enhanced at specific ratios. Given the observations, the pathways of NDMA formation from four PPCPs were proposed and associated with the chemical structures of PPCPs. The presences of excess nitrogen sources enhanced the NDMA formation, with ammonia being the most important species. Different structures of PPCPs affected their NDMA formation ratios during two-stage chlorination with the addition of nitrite and nitrate. By using the back-propagation neural network theory to fit the data from the early studies that discussed the optimal strategy of coagulation to remove turbidity and the formation of NDMA from herbicides in drinking water treatment processes, increasing the size of the input data elevated the… Advisors/Committee Members: Kun-Yi Lin (chair), Yu-Cheng Chou (chair), Yi-Li Lin (chair), Wei-Hsiang Chen (committee member).

Subjects/Keywords: Chlorination; Back-propagation neural network; Pre-oxidation; Drinking water treatment; N-Nitrosodimethylamine; Nitrogenous disinfection byproduct

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Xu, D. (2016). Analysis of Nitrosamine formation from Pharmaceuticals and Personal Care Products during two-stage chlorination using Back-Propagation Neural Network. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0701116-115902

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Xu, Deng-Xiang. “Analysis of Nitrosamine formation from Pharmaceuticals and Personal Care Products during two-stage chlorination using Back-Propagation Neural Network.” 2016. Thesis, NSYSU. Accessed March 07, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0701116-115902.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Xu, Deng-Xiang. “Analysis of Nitrosamine formation from Pharmaceuticals and Personal Care Products during two-stage chlorination using Back-Propagation Neural Network.” 2016. Web. 07 Mar 2021.

Vancouver:

Xu D. Analysis of Nitrosamine formation from Pharmaceuticals and Personal Care Products during two-stage chlorination using Back-Propagation Neural Network. [Internet] [Thesis]. NSYSU; 2016. [cited 2021 Mar 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0701116-115902.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Xu D. Analysis of Nitrosamine formation from Pharmaceuticals and Personal Care Products during two-stage chlorination using Back-Propagation Neural Network. [Thesis]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0701116-115902

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

15. Wang, Ting-yen. Automatic Passenger Counting System Design for Bus Using Image Processing Techniques.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2016, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0307116-213744

► This paper to design an adaptive passenger counting system is applied to the public transportation vehicle: bus. The system combines Global Positioning System (GPS) and… (more)

Subjects/Keywords: back propagation neural network; people detection; people counting; K-means cluster; background subtraction; object tracking

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wang, T. (2016). Automatic Passenger Counting System Design for Bus Using Image Processing Techniques. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0307116-213744

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wang, Ting-yen. “Automatic Passenger Counting System Design for Bus Using Image Processing Techniques.” 2016. Thesis, NSYSU. Accessed March 07, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0307116-213744.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wang, Ting-yen. “Automatic Passenger Counting System Design for Bus Using Image Processing Techniques.” 2016. Web. 07 Mar 2021.

Vancouver:

Wang T. Automatic Passenger Counting System Design for Bus Using Image Processing Techniques. [Internet] [Thesis]. NSYSU; 2016. [cited 2021 Mar 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0307116-213744.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang T. Automatic Passenger Counting System Design for Bus Using Image Processing Techniques. [Thesis]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0307116-213744

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

16. Yeh, Huai-Jen. Application of Neural Network on the Recognition of Acoustic Signal for Engine.

Degree: Master, Physics, 2003, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0218103-113321

► Abstract The traditional fault inspection of the motorcar engine cannot detect the noise and sound signal resulted from the abnormalities of some mechanical parts. For… (more)

▼ Abstract The traditional fault inspection of the motorcar engine cannot detect the noise and sound signal resulted from the abnormalities of some mechanical parts. For instance, the cylinder misfires; the looseness of the fan belt is irregular; the valve clearance is out of orderâ¦. and so on. When the fault message cannot be delivered by the ECU of the computer, the skilled senior engineers are required at this moment to make the experiential judgments. In the present society, due to the development of information, the computer technology makes progress by leaps and bounds. If we can make use of the monitoring method by the Acoustic signal instrument, build up a set of complete and efficient fault diagnosis system through the computer software and apply speedy and accurate way to assist the repairmen in relocating the causes for such faults, the accuracy of inspection can be greatly enhanced with a huge help in the preventive maintenance work. In that case, the fault conditions of the engine can be validated precisely and effectively, so the overhaul efficiency of the engine can be upgraded to a large extent. In this article, the procedures of sound signal recording will be brought forward by linking the digital camera with such a recording equipment as the high-precision microphone to make records of the fault sounds made when the engine runs. It uses the frequency analyzer to conduct the sampling and combine the computer software to further process and analyze the same. Finally the character parameters will be obtained. By applying the mathematical exercise of âBack-Propagation Neural Networkâ to undertake the training and detection of the sounds for the purpose of identifying the kinds of the faults. It replaces the errors caused from the experiential judgments made by the expert senior engineers. In terms of the training and maintenance ability of the newly recruited technical repairmen, their capability for exact and reasonable recognition of the fault types is substantially promoted. Keywordsï¼Acoustic Signalï¼Back Propagation Neural Network Advisors/Committee Members: none (chair), none (committee member), none (chair), none (committee member).

Subjects/Keywords: Acoustic Signal; Back Propagation Neural Network

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Yeh, H. (2003). Application of Neural Network on the Recognition of Acoustic Signal for Engine. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0218103-113321

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Yeh, Huai-Jen. “Application of Neural Network on the Recognition of Acoustic Signal for Engine.” 2003. Thesis, NSYSU. Accessed March 07, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0218103-113321.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Yeh, Huai-Jen. “Application of Neural Network on the Recognition of Acoustic Signal for Engine.” 2003. Web. 07 Mar 2021.

Vancouver:

Yeh H. Application of Neural Network on the Recognition of Acoustic Signal for Engine. [Internet] [Thesis]. NSYSU; 2003. [cited 2021 Mar 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0218103-113321.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yeh H. Application of Neural Network on the Recognition of Acoustic Signal for Engine. [Thesis]. NSYSU; 2003. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0218103-113321

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

17. Hsu, Ya-wen. Development of an Intelligent Pedestrian Fall Detection System Based on Machine Vision.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2015, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0808115-035539

► Statistics shows that inpatients or residents of long-term care facilities may fall from daily activities. Most of these falls are associated with identifiable risk factors… (more)

Subjects/Keywords: Adaptive boosting algorithm (AdaBoost); Back Propagation Neural Network (BPNN); learning algorithm; fall detection; machine vision

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Hsu, Y. (2015). Development of an Intelligent Pedestrian Fall Detection System Based on Machine Vision. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0808115-035539

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Hsu, Ya-wen. “Development of an Intelligent Pedestrian Fall Detection System Based on Machine Vision.” 2015. Thesis, NSYSU. Accessed March 07, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0808115-035539.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Hsu, Ya-wen. “Development of an Intelligent Pedestrian Fall Detection System Based on Machine Vision.” 2015. Web. 07 Mar 2021.

Vancouver:

Hsu Y. Development of an Intelligent Pedestrian Fall Detection System Based on Machine Vision. [Internet] [Thesis]. NSYSU; 2015. [cited 2021 Mar 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0808115-035539.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hsu Y. Development of an Intelligent Pedestrian Fall Detection System Based on Machine Vision. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0808115-035539

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

18. Palani S. Experimental investigation of quality characteristics in macro and micro machining processes using intelligent techniques;.

Degree: Quality characteristics in macro and micro machining processes, 2014, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/17391

►

The technological advances with the ever-growing use of computer newlinecontrolled machine tools which are integrated with machine vision newlinesystem(MVS), have brought up new issues to… (more)

▼

The technological advances with the ever-growing use of computer newlinecontrolled machine tools which are integrated with machine vision newlinesystem(MVS), have brought up new issues to emphasize the need for more newlineprecise predictive models. In the macro machining operations, a novel attempt has been made newlineto predict the average surface roughness (Ra) of the turned components using newlinea differential evolution algorithm (DEA) based artificial neural network newline(ANN), applied to train feed forward multi-layer perceptron neural networks newline(MLPNN) and compared with the widely used back-propagation (BP) based newlineANN and an adaptive neuro-fuzzy inference system (ANFIS) model. It is newlinefound that the predicted values of Ra are in good agreement with the newlineexperimental values. It is also found that the error percentage is very minimal newlinein DEA based ANN and also observed that the convergence speed for the newlineANN-DEA model is higher than the ANN-BP and ANFIS. The images of milled surface grabbed by the MVS could be newlineextracted using spatial frequency domain two dimensional Fourier transform newline(2D-FT) to get the features of image texture (major peak frequency (F1), newlineprincipal component magnitude squared value (F2), and average gray level newline(Ga)). A new ANFIS is applied to predict Ra. The proposed model is verified newlineand compared by using ANN-feed forward back-propagation (ANN-FFBP) model. It is found that the average prediction error is less than that of ANNFFBP, newlineindicating that the ANFIS is more reliable than the ANN-FFBP. From newlinethe performance of ANN-FFBP and ANFIS models in terms of average newlineabsolute percentage error, it is observed that the ANFIS model outperforms newlineANN. In the second phase of work, a tool-based micro-machining process newlineis employed for automated, noncontact, and flexible prediction of quality newlineresponse characteristics such as Ra, tool wear (TW) and material removal rate newline(MRR) of micro-turned miniaturized parts through a MVS which is integrated newlinewith an ANFIS . newline

References p.165-173

Advisors/Committee Members: Natarajan U.

Subjects/Keywords: Back-propagation; Differential evolution algorithm; Machine vision system; Macro machining; Mechanical Engineering; Micro machining

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

S, P. (2014). Experimental investigation of quality characteristics in macro and micro machining processes using intelligent techniques;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/17391

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

S, Palani. “Experimental investigation of quality characteristics in macro and micro machining processes using intelligent techniques;.” 2014. Thesis, Anna University. Accessed March 07, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/17391.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

S, Palani. “Experimental investigation of quality characteristics in macro and micro machining processes using intelligent techniques;.” 2014. Web. 07 Mar 2021.

Vancouver:

S P. Experimental investigation of quality characteristics in macro and micro machining processes using intelligent techniques;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Mar 07]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/17391.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

S P. Experimental investigation of quality characteristics in macro and micro machining processes using intelligent techniques;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/17391

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Anna University

19. Jayasankar V. Neural network based monitoring and genetic algorithm based enhancement of voltage stability;.

Degree: 2013, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/10251

►

Voltage stability assessment and improvement form the core function in a modern power system operation and control. The voltage stability can be identified through various… (more)

▼

Voltage stability assessment and improvement form the core function in a modern power system operation and control. The voltage stability can be identified through various stability factors. In this work, line stability index is used to calculate the stability of each line in the considered IEEE test systems by using the conventional power flow algorithm. When this index value changes from 0 to 1, the voltage stability of the system relatively decreases. In order to improve the system voltage stability the Thyristor Controlled Series Capacitor (TCSC) is installed in the most severe line, which is identified from the line stability index. Due to the non-linear nature of the voltage stability assessment problem, neural networks can be used for voltage stability monitoring. In this work, a single Feed Forward Back Propagation Network (FFBPN) with minimal number of neurons is used. From the results obtained the severe lines are determined. The effectiveness of this method has been demonstrated on the two IEEE test systems. Based on the ranking of the lines under various load conditions, this work identifies the optimal location of TCSC among the severe lines for the voltage stability improvement. Genetic algorithm approach is also investigated for the voltage stability analysis and its enhancement. Using Genetic Algorithm (GA), the optimal line for TCSC placement and the optimal value of capacitive reactance of TCSC to be inserted are identified based on the minimization of the maximum value of line stability index under normal and under different single line contingencies with varying load conditions. Moreover, the GA parameters such as mutation rate, crossover rate and population size are also optimized in this work. This algorithm has been tested successfully on the considered IEEE test systems. From the simulation results of proposed approaches, it has been ascertained that there is considerable improvement in voltage stability after placing TCSC. newline

Appendices 1 to 2; pp. 112 to 118

Advisors/Committee Members: Kamaraj, N..

Subjects/Keywords: Neural network; genetic algorithm; Thyristor Controlled Series Capacitor; Forward Back Propagation Network

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APA (6^th Edition):

V, J. (2013). Neural network based monitoring and genetic algorithm based enhancement of voltage stability;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/10251

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

V, Jayasankar. “Neural network based monitoring and genetic algorithm based enhancement of voltage stability;.” 2013. Thesis, Anna University. Accessed March 07, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/10251.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

V, Jayasankar. “Neural network based monitoring and genetic algorithm based enhancement of voltage stability;.” 2013. Web. 07 Mar 2021.

Vancouver:

V J. Neural network based monitoring and genetic algorithm based enhancement of voltage stability;. [Internet] [Thesis]. Anna University; 2013. [cited 2021 Mar 07]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/10251.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

V J. Neural network based monitoring and genetic algorithm based enhancement of voltage stability;. [Thesis]. Anna University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/10251

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Anna University

20. Ravikumar G. Compiler directed disk seek algorithm for power optimization in large disk based system using soft computing techniques;.

Degree: Disk-seek algorithm for power optimization in large disk based system using soft computing techniques, 2014, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/24188

►

The recent developments and an extensive growth of applications viz Internet based servers interactive television video conferencing etc require large volume of multidimensional data stored… (more)

Subjects/Keywords: Back Propagation Neural Network; Disk-seek algorithm; Information and communication engineering; Levenberg Morquardt algorithm

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APA (6^th Edition):

G, R. (2014). Compiler directed disk seek algorithm for power optimization in large disk based system using soft computing techniques;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/24188

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

G, Ravikumar. “Compiler directed disk seek algorithm for power optimization in large disk based system using soft computing techniques;.” 2014. Thesis, Anna University. Accessed March 07, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/24188.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

G, Ravikumar. “Compiler directed disk seek algorithm for power optimization in large disk based system using soft computing techniques;.” 2014. Web. 07 Mar 2021.

Vancouver:

G R. Compiler directed disk seek algorithm for power optimization in large disk based system using soft computing techniques;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Mar 07]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/24188.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

G R. Compiler directed disk seek algorithm for power optimization in large disk based system using soft computing techniques;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/24188

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Addis Ababa University

21. Sewnet, Getnet. Predictive Modelling of kaliti Wastewater Treatment Plant Performance Using Artificial Neural Networks .

Degree: 2012, Addis Ababa University

URL: http://etd.aau.edu.et/dspace/handle/123456789/4654

► Artificial neural networks are a form of artificial intelligence that have the capability of learning, growing, and adapting within dynamic environments. A reliable model for… (more)

▼ Artificial neural networks are a form of artificial intelligence that have the capability of learning, growing, and adapting within dynamic environments. A reliable model for any wastewater treatment plant is essential in order to provide a tool for predicting its performance and to form a basis for controlling the operation of the process. This would enable to assess the stability of environmental balance at minimized operational costs. Wastewater treatment process is complex and attains a high degree of nonlinearity due to the presence of bio-organic constituents that are difficult to model using mechanistic approaches. Predicting the plant operational parameters using conventional experimental techniques is also a time consuming step and is an obstacle in the way of efficient control of such processes. In this work, a soft computing approach based on back propagation artificial neural networks, which employed genetic algorithm and partial mutual information to perform input selection, was used to acquire the knowledge base of Kaliti wastewater treatment plant and has been applied for predicting and optimizing selected plant performance variables viz. pH, BOD5, COD, NH3, and TDS effluent concentration of the plant. In the model structure of the treatment plant performance, two different functional structures in the configuration of the network are constructed and compared. In the first configuration Multiple-Input-Single-Output (MISO), structures differing in the type of data used, raw operational data and outlier removed data in the input layer, are used to build models for each of the five performance indicators selected in this work. Partial Mutual Information-based Input Selection (PMIS) and Genetic Algorithm (GA) based input selection algorithms are applied for both above mentioned MISO configuration based models. In the second configuration Multiple-Input-Multiple-Output (MIMO), GA based input selection is applied for both the raw and outlier removed data. The model performance was evaluated with statistical parameters and the simulation results indicates that the MISO modelling approach achieves much more accurate predictions as compared with the MIMO modelling approach. Optimum model architecture of 14-43-1 for pH, 16-29-1 for BOD5, 14-50-1 for COD, 6-28-1 for NH3, and 10-48-1 for TDS were selected for predicting the performance of Kaliti wastewater treatment plant using MISO configuration. The linear correlation between predicted outputs and target outputs for the optimum model architecture described above are 0.97 for pH, 0.94 for BOD5, 0.98 for COD, 0.94 for NH3, and 0.98 for TDS. Advisors/Committee Members: Dr.-Ing Berhanu Assefa (advisor).

Subjects/Keywords: Artificial neural networks; Back propagation; Genetic algorithm; Partial mutual information; Wastewater treatment

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sewnet, G. (2012). Predictive Modelling of kaliti Wastewater Treatment Plant Performance Using Artificial Neural Networks . (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/4654

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sewnet, Getnet. “Predictive Modelling of kaliti Wastewater Treatment Plant Performance Using Artificial Neural Networks .” 2012. Thesis, Addis Ababa University. Accessed March 07, 2021. http://etd.aau.edu.et/dspace/handle/123456789/4654.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sewnet, Getnet. “Predictive Modelling of kaliti Wastewater Treatment Plant Performance Using Artificial Neural Networks .” 2012. Web. 07 Mar 2021.

Vancouver:

Sewnet G. Predictive Modelling of kaliti Wastewater Treatment Plant Performance Using Artificial Neural Networks . [Internet] [Thesis]. Addis Ababa University; 2012. [cited 2021 Mar 07]. Available from: http://etd.aau.edu.et/dspace/handle/123456789/4654.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sewnet G. Predictive Modelling of kaliti Wastewater Treatment Plant Performance Using Artificial Neural Networks . [Thesis]. Addis Ababa University; 2012. Available from: http://etd.aau.edu.et/dspace/handle/123456789/4654

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Addis Ababa University

22. Sewnet, Getnet. PREDICTIVE MODELLING OF KALITI WASTEWATER TREATMENT PLANT PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS .

Degree: 2012, Addis Ababa University

URL: http://etd.aau.edu.et/dspace/handle/123456789/3955

► Artificial neural networks are a form of artificial intelligence that have the capability of learning, growing, and adapting within dynamic environments. A reliable model for… (more)

▼ Artificial neural networks are a form of artificial intelligence that have the capability of learning, growing, and adapting within dynamic environments. A reliable model for any wastewater treatment plant is essential in order to provide a tool for predicting its performance and to form a basis for controlling the operation of the process. This would enable to assess the stability of environmental balance at minimized operational costs. Wastewater treatment process is complex and attains a high degree of nonlinearity due to the presence of bio-organic constituents that are difficult to model using mechanistic approaches. Predicting the plant operational parameters using conventional experimental techniques is also a time consuming step and is an obstacle in the way of efficient control of such processes. In this work, a soft computing approach based on back propagation artificial neural networks, which employed genetic algorithm and partial mutual information to perform input selection, was used to acquire the knowledge base of Kaliti wastewater treatment plant and has been applied for predicting and optimizing selected plant performance variables viz. pH, BOD5, COD, NH3, and TDS effluent concentration of the plant. In the model structure of the treatment plant performance, two different functional structures in the configuration of the network are constructed and compared. In the first configuration Multiple-Input-Single-Output (MISO), structures differing in the type of data used, raw operational data and outlier removed data in the input layer, are used to build models for each of the five performance indicators selected in this work. Partial Mutual Information-based Input Selection (PMIS) and Genetic Algorithm (GA) based input selection algorithms are applied for both above mentioned MISO configuration based models. In the second configuration Multiple-Input-Multiple-Output (MIMO), GA based input selection is applied for both the raw and outlier removed data. The model performance was evaluated with statistical parameters and the simulation results indicates that the MISO modelling approach achieves much more accurate predictions as compared with the MIMO modelling approach. Optimum model architecture of 14-43-1 for pH, 16-29-1 for BOD5, 14-50-1 for COD, 6-28-1 for NH3, and 10-48-1 for TDS were selected for predicting the performance of Kaliti wastewater treatment plant using MISO configuration. The linear correlation between predicted outputs and target outputs for the optimum model architecture described above are 0.97 for pH, 0.94 for BOD5, 0.98 for COD, 0.94 for NH3, and 0.98 for TDS. Advisors/Committee Members: Dr.-Ing Berhanu Assefa (advisor).

Subjects/Keywords: Artificial neural networks; Back propagation; Genetic algorithm; Partial mutual information; Wastewater treatment

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sewnet, G. (2012). PREDICTIVE MODELLING OF KALITI WASTEWATER TREATMENT PLANT PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS . (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/3955

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sewnet, Getnet. “PREDICTIVE MODELLING OF KALITI WASTEWATER TREATMENT PLANT PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS .” 2012. Thesis, Addis Ababa University. Accessed March 07, 2021. http://etd.aau.edu.et/dspace/handle/123456789/3955.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sewnet, Getnet. “PREDICTIVE MODELLING OF KALITI WASTEWATER TREATMENT PLANT PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS .” 2012. Web. 07 Mar 2021.

Vancouver:

Sewnet G. PREDICTIVE MODELLING OF KALITI WASTEWATER TREATMENT PLANT PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS . [Internet] [Thesis]. Addis Ababa University; 2012. [cited 2021 Mar 07]. Available from: http://etd.aau.edu.et/dspace/handle/123456789/3955.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sewnet G. PREDICTIVE MODELLING OF KALITI WASTEWATER TREATMENT PLANT PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS . [Thesis]. Addis Ababa University; 2012. Available from: http://etd.aau.edu.et/dspace/handle/123456789/3955

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Nairobi

23. Mbirika, Douglas H. A type-2 diabetes early warning system using particle swarm optimized artificial neural networks: a case of trans Nzoia county of Kenya .

Degree: 2014, University of Nairobi

URL: http://hdl.handle.net/11295/76655

► This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among… (more)

Subjects/Keywords: Artificial Neural Networks; Particle Swarm Optimization; Back Propagation Algorithm; Type 2 Diabetes

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Mbirika, D. H. (2014). A type-2 diabetes early warning system using particle swarm optimized artificial neural networks: a case of trans Nzoia county of Kenya . (Thesis). University of Nairobi. Retrieved from http://hdl.handle.net/11295/76655

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mbirika, Douglas H. “A type-2 diabetes early warning system using particle swarm optimized artificial neural networks: a case of trans Nzoia county of Kenya .” 2014. Thesis, University of Nairobi. Accessed March 07, 2021. http://hdl.handle.net/11295/76655.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mbirika, Douglas H. “A type-2 diabetes early warning system using particle swarm optimized artificial neural networks: a case of trans Nzoia county of Kenya .” 2014. Web. 07 Mar 2021.

Vancouver:

Mbirika DH. A type-2 diabetes early warning system using particle swarm optimized artificial neural networks: a case of trans Nzoia county of Kenya . [Internet] [Thesis]. University of Nairobi; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11295/76655.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mbirika DH. A type-2 diabetes early warning system using particle swarm optimized artificial neural networks: a case of trans Nzoia county of Kenya . [Thesis]. University of Nairobi; 2014. Available from: http://hdl.handle.net/11295/76655

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Virginia Commonwealth University

24. Albarakati, Noor. FAST NEURAL NETWORK ALGORITHM FOR SOLVING CLASSIFICATION TASKS.

Degree: MS, Computer Science, 2012, Virginia Commonwealth University

URL: https://doi.org/10.25772/F3ZW-P786 ; https://scholarscompass.vcu.edu/etd/2740

► Classification is one-out-of several applications in the neural network (NN) world. Multilayer perceptron (MLP) is the common neural network architecture which is used for classification… (more)

Subjects/Keywords: Classification; Error Back Propagation; Multilayer Perceptron; Neural Network; Computer Sciences; Physical Sciences and Mathematics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Albarakati, N. (2012). FAST NEURAL NETWORK ALGORITHM FOR SOLVING CLASSIFICATION TASKS. (Thesis). Virginia Commonwealth University. Retrieved from https://doi.org/10.25772/F3ZW-P786 ; https://scholarscompass.vcu.edu/etd/2740

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Albarakati, Noor. “FAST NEURAL NETWORK ALGORITHM FOR SOLVING CLASSIFICATION TASKS.” 2012. Thesis, Virginia Commonwealth University. Accessed March 07, 2021. https://doi.org/10.25772/F3ZW-P786 ; https://scholarscompass.vcu.edu/etd/2740.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Albarakati, Noor. “FAST NEURAL NETWORK ALGORITHM FOR SOLVING CLASSIFICATION TASKS.” 2012. Web. 07 Mar 2021.

Vancouver:

Albarakati N. FAST NEURAL NETWORK ALGORITHM FOR SOLVING CLASSIFICATION TASKS. [Internet] [Thesis]. Virginia Commonwealth University; 2012. [cited 2021 Mar 07]. Available from: https://doi.org/10.25772/F3ZW-P786 ; https://scholarscompass.vcu.edu/etd/2740.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Albarakati N. FAST NEURAL NETWORK ALGORITHM FOR SOLVING CLASSIFICATION TASKS. [Thesis]. Virginia Commonwealth University; 2012. Available from: https://doi.org/10.25772/F3ZW-P786 ; https://scholarscompass.vcu.edu/etd/2740

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Guelph

25. Cheung, Edwin H. Equine Gait Data Analysis using Signal Transforms as a Preprocessor to Back Propagation Networks.

Degree: MS, School of Computer Science, 2014, University of Guelph

URL: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8150

► This thesis examines using Back Propagation network in the analysis of equine gait data. Back Propagation networks are capable of classifying non-linear data sets, but… (more)

Subjects/Keywords: Equine Gait; Neural Network; Fourier Transform; Gait Analysis; Signal Transform; Wavelet Transform; Back Propagation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cheung, E. H. (2014). Equine Gait Data Analysis using Signal Transforms as a Preprocessor to Back Propagation Networks. (Masters Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8150

Chicago Manual of Style (16^th Edition):

Cheung, Edwin H. “Equine Gait Data Analysis using Signal Transforms as a Preprocessor to Back Propagation Networks.” 2014. Masters Thesis, University of Guelph. Accessed March 07, 2021. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8150.

MLA Handbook (7^th Edition):

Cheung, Edwin H. “Equine Gait Data Analysis using Signal Transforms as a Preprocessor to Back Propagation Networks.” 2014. Web. 07 Mar 2021.

Vancouver:

Cheung EH. Equine Gait Data Analysis using Signal Transforms as a Preprocessor to Back Propagation Networks. [Internet] [Masters thesis]. University of Guelph; 2014. [cited 2021 Mar 07]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8150.

Council of Science Editors:

Cheung EH. Equine Gait Data Analysis using Signal Transforms as a Preprocessor to Back Propagation Networks. [Masters Thesis]. University of Guelph; 2014. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8150

University of Tennessee – Knoxville

26. Zhao, Jiajia. Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks.

Degree: MS, Computer Science, 2019, University of Tennessee – Knoxville

URL: https://trace.tennessee.edu/utk_gradthes/5536

► A deep neural network is a non-spiking artificial neural network which uses multiple structured layers to extract features from the input. Spiking neural networks are… (more)

Subjects/Keywords: Spiking Neural Network; Deep Neural Network; Spiking Deep Neural Network; Machine Learning; Back Propagation; Tensorflow

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zhao, J. (2019). Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/5536

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zhao, Jiajia. “Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks.” 2019. Thesis, University of Tennessee – Knoxville. Accessed March 07, 2021. https://trace.tennessee.edu/utk_gradthes/5536.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zhao, Jiajia. “Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks.” 2019. Web. 07 Mar 2021.

Vancouver:

Zhao J. Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks. [Internet] [Thesis]. University of Tennessee – Knoxville; 2019. [cited 2021 Mar 07]. Available from: https://trace.tennessee.edu/utk_gradthes/5536.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhao J. Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks. [Thesis]. University of Tennessee – Knoxville; 2019. Available from: https://trace.tennessee.edu/utk_gradthes/5536

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

KTH

27. Guan, Xing. Predict Next Location of Users using Deep Learning.

Degree: Electrical Engineering and Computer Science (EECS), 2019, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263620

►

Predicting the next location of a user has been interesting for both academia and industry. Applications like location-based advertising, traffic planning, intelligent resource allocation… (more)

▼

Predicting the next location of a user has been interesting for both academia and industry. Applications like location-based advertising, traffic planning, intelligent resource allocation as well as in recommendation services are some of the problems that many are interested in solving. Along with the technological advancement and the widespread usage of electronic devices, many location-based records are created. Today, deep learning framework has successfully surpassed many conventional methods in many learning tasks, most known in the areas of image and voice recognition. One of the neural network architecture that has shown the promising result at sequential data is Recurrent Neural Network (RNN). Since the creation of RNN, much alternative architecture have been proposed, and architectures like Long Short Term Memory (LSTM) and Gated Recurrent Units (GRU) are one of the popular ones that are created[5]. This thesis uses GRU architecture and features that incorporate time and location into the network to forecast people’s next location In this paper, a spatial-temporal neural network (ST-GRU) has been proposed. It can be seen as two parts, which are ST and GRU. The first part is a feature extraction algorithm that pulls out the information from a trajectory into location sequences. That process transforms the trajectory into a friendly sequence format in order to feed into the model. The second part, GRU is proposed to predict the next location given a user’s trajectory. The study shows that the proposed model ST-GRU has the best results comparing the baseline models.

Att förutspå vart en individ är på väg har varit intressant för både akademin och industrin. Tillämpningar såsom platsbaserad annonsering, trafikplanering, intelligent resursallokering samt rekommendationstjänster är några av de problem som många är intresserade av att lösa. Tillsammans med den tekniska utvecklingen och den omfattande användningen av elektroniska enheter har många platsbaserade data skapats. Idag har tekniken djupinlärning framgångsrikt överträffat många konventionella metoder i inlärningsuppgifter, bland annat inom områdena bild och röstigenkänning. En neural nätverksarkitektur som har visat lovande resultat med sekventiella data kallas återkommande neurala nätverk (RNN). Sedan skapandet av RNN har många alternativa arkitekturer skapats, bland de mest kända är Long Short Term Memory (LSTM) och Gated Recurrent Units (GRU). Den här studien använder en modifierad GRU där man bland annat lägger till attribut såsom tid och distans i nätverket för att prognostisera nästa plats. I det här examensarbetet har ett rumsligt temporalt neuralt nätverk (ST-GRU) föreslagits. Den består av två delar, nämligen ST och GRU. Den första delen är en extraktionsalgoritm som drar ut relevanta korrelationer mellan tid och plats som är inkorporerade i nätverket. Den andra delen, GRU, förutspår nästa plats med avseende på användarens aktuella plats. Studien visar att den föreslagna modellen ST-GRU ger bättre resultat…

Subjects/Keywords: Back-Propagation Algorithm; Neural Network; GRU; Recurrent; Computer and Information Sciences; Data- och informationsvetenskap

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Guan, X. (2019). Predict Next Location of Users using Deep Learning. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263620

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Guan, Xing. “Predict Next Location of Users using Deep Learning.” 2019. Thesis, KTH. Accessed March 07, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263620.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Guan, Xing. “Predict Next Location of Users using Deep Learning.” 2019. Web. 07 Mar 2021.

Vancouver:

Guan X. Predict Next Location of Users using Deep Learning. [Internet] [Thesis]. KTH; 2019. [cited 2021 Mar 07]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263620.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Guan X. Predict Next Location of Users using Deep Learning. [Thesis]. KTH; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263620

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

McMaster University

28. Bidaki, Elham. ANALYSIS AND DESIGN OF NONLINEAR FIBER OPTIC COMMUNICATION SYSTEMS.

Degree: PhD, 2020, McMaster University

URL: http://hdl.handle.net/11375/25794

►

Fiber-optic systems represent the backbone of the communication networks, carrying most of the world’s data traffic. The main bottleneck in today’s fiber-optic communication systems has… (more)

▼

Fiber-optic systems represent the backbone of the communication networks, carrying most of the world’s data traffic. The main bottleneck in today’s fiber-optic communication systems has roots in the inherent nonlinearity of the fiber. Hence, developing new transmission schemes that are compatible with the nonlinear behavior of the optical fiber has become necessary. To utilize the full transmission capacity of an optical fiber, this thesis investigates two different techniques – compensation-based method and nonlinear Fourier transform (NFT). For the purpose of suppressing the nonlinear distortion in real time, an optical back propagation (OBP) technique using Raman pumped dispersion compensating fibers (DCF). OBP, as an all-optical signal processing technique, can compensate for both intra- and inter-channel nonlinear impairments in real time in point-to-point systems as well as in optical networks. The proposed inline OBP module consists of an optical phase conjugator (OPC), amplifiers and a Raman pumped DCF. In order to suppress the nonlinear effects of the transmission fiber, the power in the OBP fiber should increase exponentially with distance. This can be approximately achieved by using Raman pumping of the backpropagation fiber. Simulation results show that this technique provides 7.7 dB performance improvement in Q-factor over conventional systems. The second part of this thesis is dedicated to the NFT as a promising framework to exploit the inherent nonlinearity of optical fiber rather than treating it as an undesirable effect and using perturbation and approximation-based methods to mitigate it. A novel multistage perturbation technique to realize the NFT as a cascade of linear discrete Fourier transforms is developed. The linear Fourier transform can be easily implemented in the optical domain using a time lens or discrete photonic components, which can be implemented in silicon photonics. The proposed technique provides a promising way to implement NFT in the optical domain, which will fully utilize the potential of NFT for wavelength-division multiplexed fiber-optic systems in the optical domain. Moreover, a nonlinear frequency-division multiplexed (NFDM) transmission scheme with midpoint OPC is investigated. The proposed mid-OPC NFDM system offers a degree of freedom to have a flexible power normalization factor, P_n to minimize the signal-noise mixing in NFT processing for a specific launch power, resulting in significant system performance improvement up to 5.6 dB in Q-factor over conventional NFDM systems. Another advantage of the proposed scheme is that the mid-OPC NFDM system extends the transmission reach without having to increase the guard interval, which leads to higher spectral efficiency.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Kumar, Shiva, Electrical and Computer Engineering.

Subjects/Keywords: Nonlinear optics; Fiber optic communication systems; Nonlinear Fourier transform; Optical back propagation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Bidaki, E. (2020). ANALYSIS AND DESIGN OF NONLINEAR FIBER OPTIC COMMUNICATION SYSTEMS. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/25794

Chicago Manual of Style (16^th Edition):

Bidaki, Elham. “ANALYSIS AND DESIGN OF NONLINEAR FIBER OPTIC COMMUNICATION SYSTEMS.” 2020. Doctoral Dissertation, McMaster University. Accessed March 07, 2021. http://hdl.handle.net/11375/25794.

MLA Handbook (7^th Edition):

Bidaki, Elham. “ANALYSIS AND DESIGN OF NONLINEAR FIBER OPTIC COMMUNICATION SYSTEMS.” 2020. Web. 07 Mar 2021.

Vancouver:

Bidaki E. ANALYSIS AND DESIGN OF NONLINEAR FIBER OPTIC COMMUNICATION SYSTEMS. [Internet] [Doctoral dissertation]. McMaster University; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11375/25794.

Council of Science Editors:

Bidaki E. ANALYSIS AND DESIGN OF NONLINEAR FIBER OPTIC COMMUNICATION SYSTEMS. [Doctoral Dissertation]. McMaster University; 2020. Available from: http://hdl.handle.net/11375/25794

NSYSU

29. Tan, Zjeng-Ming. A Study On Video Servo Control Systems.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2007, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716107-173628

► In this research, a single PAN-TILT image servo system has been developed with real-time face tracing technology. First, the target face is detected, and then… (more)

Subjects/Keywords: Back-propagation neural network; video servo system; image tracking

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Tan, Z. (2007). A Study On Video Servo Control Systems. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716107-173628

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Tan, Zjeng-Ming. “A Study On Video Servo Control Systems.” 2007. Thesis, NSYSU. Accessed March 07, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716107-173628.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Tan, Zjeng-Ming. “A Study On Video Servo Control Systems.” 2007. Web. 07 Mar 2021.

Vancouver:

Tan Z. A Study On Video Servo Control Systems. [Internet] [Thesis]. NSYSU; 2007. [cited 2021 Mar 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716107-173628.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tan Z. A Study On Video Servo Control Systems. [Thesis]. NSYSU; 2007. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716107-173628

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Anna University

30. Sathiyasekar K. Predicting the insulation status of High voltage rotating machines Using intelligent techniques;.

Degree: Predicting the insulation status of High voltage rotating machines Using intelligent techniques, 2014, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/28422

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High voltage rotating machines are widely used in the power newlineStations sugar mills steel mills cement mills etc Insulation is an essential newlinecomponent for proper… (more)

Subjects/Keywords: Adaptive Neuro Fuzzy Inference System; Back Propagation Neural; Fuzzy logic approach; High voltage rotating machines; Proportional Integral and Derivative

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

K, S. (2014). Predicting the insulation status of High voltage rotating machines Using intelligent techniques;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28422

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

K, Sathiyasekar. “Predicting the insulation status of High voltage rotating machines Using intelligent techniques;.” 2014. Thesis, Anna University. Accessed March 07, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/28422.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

K, Sathiyasekar. “Predicting the insulation status of High voltage rotating machines Using intelligent techniques;.” 2014. Web. 07 Mar 2021.

Vancouver:

K S. Predicting the insulation status of High voltage rotating machines Using intelligent techniques;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Mar 07]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28422.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

K S. Predicting the insulation status of High voltage rotating machines Using intelligent techniques;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28422

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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Open Access Theses and Dissertations