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You searched for subject:(Artificial neural network). Showing records 1 – 30 of 942 total matches.

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Penn State University

1. Da, Lina. SCREENING AND DESIGN CRITERIA FOR DIFFERENT SLANTED WELLS.

Degree: 2018, Penn State University

 Since the development of the oil industry, engineers have been working to improve the production of wells. In order to maximize the production of a… (more)

Subjects/Keywords: Artificial Neural Network

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APA (6th Edition):

Da, L. (2018). SCREENING AND DESIGN CRITERIA FOR DIFFERENT SLANTED WELLS. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/13008dul188

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

Chicago Manual of Style (16th Edition):

Da, Lina. “SCREENING AND DESIGN CRITERIA FOR DIFFERENT SLANTED WELLS.” 2018. Thesis, Penn State University. Accessed September 24, 2020. https://submit-etda.libraries.psu.edu/catalog/13008dul188.

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

MLA Handbook (7th Edition):

Da, Lina. “SCREENING AND DESIGN CRITERIA FOR DIFFERENT SLANTED WELLS.” 2018. Web. 24 Sep 2020.

Vancouver:

Da L. SCREENING AND DESIGN CRITERIA FOR DIFFERENT SLANTED WELLS. [Internet] [Thesis]. Penn State University; 2018. [cited 2020 Sep 24]. Available from: https://submit-etda.libraries.psu.edu/catalog/13008dul188.

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

Council of Science Editors:

Da L. SCREENING AND DESIGN CRITERIA FOR DIFFERENT SLANTED WELLS. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/13008dul188

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


University of Waterloo

2. Wang, Han. Modelling and Optimization of a Pilot-Scale Entrained Flow gasifier using Artificial Neural Networks.

Degree: 2020, University of Waterloo

 In this research, the construction and validation of both ANN and RNN models was presented to accurately and efficiently predict both steady state and dynamic… (more)

Subjects/Keywords: modeling; gasifier; artificial neural network

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APA (6th Edition):

Wang, H. (2020). Modelling and Optimization of a Pilot-Scale Entrained Flow gasifier using Artificial Neural Networks. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15681

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

Chicago Manual of Style (16th Edition):

Wang, Han. “Modelling and Optimization of a Pilot-Scale Entrained Flow gasifier using Artificial Neural Networks.” 2020. Thesis, University of Waterloo. Accessed September 24, 2020. http://hdl.handle.net/10012/15681.

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

MLA Handbook (7th Edition):

Wang, Han. “Modelling and Optimization of a Pilot-Scale Entrained Flow gasifier using Artificial Neural Networks.” 2020. Web. 24 Sep 2020.

Vancouver:

Wang H. Modelling and Optimization of a Pilot-Scale Entrained Flow gasifier using Artificial Neural Networks. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Sep 24]. Available from: http://hdl.handle.net/10012/15681.

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

Council of Science Editors:

Wang H. Modelling and Optimization of a Pilot-Scale Entrained Flow gasifier using Artificial Neural Networks. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15681

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


University of Nairobi

3. Onyango, Paschal O. Maize crop yield prediction through reinforcement learning, artificial neural network and alert messages generation .

Degree: 2012, University of Nairobi

 Most of the medium and small-scale Kenyan farmers rely on metrological department for weather information and subsequently also rely on the ministry of agriculture to… (more)

Subjects/Keywords: Maize Crop; Artificial Neural Network

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APA (6th Edition):

Onyango, P. O. (2012). Maize crop yield prediction through reinforcement learning, artificial neural network and alert messages generation . (Thesis). University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/23395

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

Chicago Manual of Style (16th Edition):

Onyango, Paschal O. “Maize crop yield prediction through reinforcement learning, artificial neural network and alert messages generation .” 2012. Thesis, University of Nairobi. Accessed September 24, 2020. http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/23395.

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

MLA Handbook (7th Edition):

Onyango, Paschal O. “Maize crop yield prediction through reinforcement learning, artificial neural network and alert messages generation .” 2012. Web. 24 Sep 2020.

Vancouver:

Onyango PO. Maize crop yield prediction through reinforcement learning, artificial neural network and alert messages generation . [Internet] [Thesis]. University of Nairobi; 2012. [cited 2020 Sep 24]. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/23395.

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

Council of Science Editors:

Onyango PO. Maize crop yield prediction through reinforcement learning, artificial neural network and alert messages generation . [Thesis]. University of Nairobi; 2012. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/23395

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


University of Manitoba

4. Bhide, Ashlesha. An Artificial neural network-based signal classifier for automated identification of detection signals from a dielectrophoretic cytometer.

Degree: Electrical and Computer Engineering, 2014, University of Manitoba

 An automated signal classifier and a semi-automated signal identifier are designed for collecting the dielectrophoretic signatures of cells flowing through a dielectrophoretic cytometer. In past… (more)

Subjects/Keywords: Artificial Neural Network; DEP

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APA (6th Edition):

Bhide, A. (2014). An Artificial neural network-based signal classifier for automated identification of detection signals from a dielectrophoretic cytometer. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/23318

Chicago Manual of Style (16th Edition):

Bhide, Ashlesha. “An Artificial neural network-based signal classifier for automated identification of detection signals from a dielectrophoretic cytometer.” 2014. Masters Thesis, University of Manitoba. Accessed September 24, 2020. http://hdl.handle.net/1993/23318.

MLA Handbook (7th Edition):

Bhide, Ashlesha. “An Artificial neural network-based signal classifier for automated identification of detection signals from a dielectrophoretic cytometer.” 2014. Web. 24 Sep 2020.

Vancouver:

Bhide A. An Artificial neural network-based signal classifier for automated identification of detection signals from a dielectrophoretic cytometer. [Internet] [Masters thesis]. University of Manitoba; 2014. [cited 2020 Sep 24]. Available from: http://hdl.handle.net/1993/23318.

Council of Science Editors:

Bhide A. An Artificial neural network-based signal classifier for automated identification of detection signals from a dielectrophoretic cytometer. [Masters Thesis]. University of Manitoba; 2014. Available from: http://hdl.handle.net/1993/23318


Kansas State University

5. Clayton, Jacob. Examining Bindley Field, Hodgeman County Kansas and surrounding areas for productive lithofacies using an artificial neural network model.

Degree: MS, Department of Geology, 2018, Kansas State University

 The Meramec member of Mississippian age is a proficient oil and gas producing formation within the midcontinent region of the United States. It is produced… (more)

Subjects/Keywords: Artificial neural network; Mississippian; Meramec

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APA (6th Edition):

Clayton, J. (2018). Examining Bindley Field, Hodgeman County Kansas and surrounding areas for productive lithofacies using an artificial neural network model. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/38547

Chicago Manual of Style (16th Edition):

Clayton, Jacob. “Examining Bindley Field, Hodgeman County Kansas and surrounding areas for productive lithofacies using an artificial neural network model.” 2018. Masters Thesis, Kansas State University. Accessed September 24, 2020. http://hdl.handle.net/2097/38547.

MLA Handbook (7th Edition):

Clayton, Jacob. “Examining Bindley Field, Hodgeman County Kansas and surrounding areas for productive lithofacies using an artificial neural network model.” 2018. Web. 24 Sep 2020.

Vancouver:

Clayton J. Examining Bindley Field, Hodgeman County Kansas and surrounding areas for productive lithofacies using an artificial neural network model. [Internet] [Masters thesis]. Kansas State University; 2018. [cited 2020 Sep 24]. Available from: http://hdl.handle.net/2097/38547.

Council of Science Editors:

Clayton J. Examining Bindley Field, Hodgeman County Kansas and surrounding areas for productive lithofacies using an artificial neural network model. [Masters Thesis]. Kansas State University; 2018. Available from: http://hdl.handle.net/2097/38547

6. Mauricio Corrêa de Almeida. Sistema tutor monitorado por rede neural artificial.

Degree: 2006, Federal University of Uberlândia

Os sistemas de ensino a distância tem recebido cada vez mais apoio para pesquisa e desenvolvimento por proporcionarem vantagens tais como: reduzir os problemas causados… (more)

Subjects/Keywords: ENGENHARIA ELETRICA; Rede neural artificial; Sistemas tutores; Rede neural de retropropagação; Inteligência artificial; Artificial neural network; Tutoring systems; Backpropagation neural network

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APA (6th Edition):

Almeida, M. C. d. (2006). Sistema tutor monitorado por rede neural artificial. (Thesis). Federal University of Uberlândia. Retrieved from http://www.bdtd.ufu.br//tde_busca/arquivo.php?codArquivo=591 ; http://www.bdtd.ufu.br//tde_busca/arquivo.php?codArquivo=592

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

Chicago Manual of Style (16th Edition):

Almeida, Mauricio Corrêa de. “Sistema tutor monitorado por rede neural artificial.” 2006. Thesis, Federal University of Uberlândia. Accessed September 24, 2020. http://www.bdtd.ufu.br//tde_busca/arquivo.php?codArquivo=591 ; http://www.bdtd.ufu.br//tde_busca/arquivo.php?codArquivo=592.

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

MLA Handbook (7th Edition):

Almeida, Mauricio Corrêa de. “Sistema tutor monitorado por rede neural artificial.” 2006. Web. 24 Sep 2020.

Vancouver:

Almeida MCd. Sistema tutor monitorado por rede neural artificial. [Internet] [Thesis]. Federal University of Uberlândia; 2006. [cited 2020 Sep 24]. Available from: http://www.bdtd.ufu.br//tde_busca/arquivo.php?codArquivo=591 ; http://www.bdtd.ufu.br//tde_busca/arquivo.php?codArquivo=592.

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

Council of Science Editors:

Almeida MCd. Sistema tutor monitorado por rede neural artificial. [Thesis]. Federal University of Uberlândia; 2006. Available from: http://www.bdtd.ufu.br//tde_busca/arquivo.php?codArquivo=591 ; http://www.bdtd.ufu.br//tde_busca/arquivo.php?codArquivo=592

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


Anna University

7. Muthukumaran, S. Investigations on neural network models for short term load forecasting; -.

Degree: Information and Communication Engineering, 2014, Anna University

Optimal day to day operation of electric power generating plants is very essential for any power utility organization to reduce input costs and the prices… (more)

Subjects/Keywords: Artificial Neural Network; Information and communication engineering; Neural network

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APA (6th Edition):

Muthukumaran, S. (2014). Investigations on neural network models for short term load forecasting; -. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/23908

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

Chicago Manual of Style (16th Edition):

Muthukumaran, S. “Investigations on neural network models for short term load forecasting; -.” 2014. Thesis, Anna University. Accessed September 24, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/23908.

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

MLA Handbook (7th Edition):

Muthukumaran, S. “Investigations on neural network models for short term load forecasting; -.” 2014. Web. 24 Sep 2020.

Vancouver:

Muthukumaran S. Investigations on neural network models for short term load forecasting; -. [Internet] [Thesis]. Anna University; 2014. [cited 2020 Sep 24]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/23908.

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

Council of Science Editors:

Muthukumaran S. Investigations on neural network models for short term load forecasting; -. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/23908

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


Penn State University

8. Enab, Khaled Ahmed. Artificial Neural Network Based Design Network For Dual Lateral Well Applications.

Degree: 2012, Penn State University

Artificial neural networks (ANNs) have become an important tool for the petroleum industry, for performance analysis of reservoirs, because their ability of understanding highly non-linear… (more)

Subjects/Keywords: Artificial Neural Network; Neural Network; Dual Lateral; Multi lateral well

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APA (6th Edition):

Enab, K. A. (2012). Artificial Neural Network Based Design Network For Dual Lateral Well Applications. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/15464

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

Chicago Manual of Style (16th Edition):

Enab, Khaled Ahmed. “Artificial Neural Network Based Design Network For Dual Lateral Well Applications.” 2012. Thesis, Penn State University. Accessed September 24, 2020. https://submit-etda.libraries.psu.edu/catalog/15464.

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

MLA Handbook (7th Edition):

Enab, Khaled Ahmed. “Artificial Neural Network Based Design Network For Dual Lateral Well Applications.” 2012. Web. 24 Sep 2020.

Vancouver:

Enab KA. Artificial Neural Network Based Design Network For Dual Lateral Well Applications. [Internet] [Thesis]. Penn State University; 2012. [cited 2020 Sep 24]. Available from: https://submit-etda.libraries.psu.edu/catalog/15464.

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

Council of Science Editors:

Enab KA. Artificial Neural Network Based Design Network For Dual Lateral Well Applications. [Thesis]. Penn State University; 2012. Available from: https://submit-etda.libraries.psu.edu/catalog/15464

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


University of Sydney

9. Li, Qing. Medical image analysis with neural network and deep learning .

Degree: 2016, University of Sydney

 Thanks to the advance of biomedical imaging systems, large volumes of biomedical image data are generated rapidly. However many doctors still rely on time consuming… (more)

Subjects/Keywords: Medical Imaging; Deep Learning; Artificial Neural Network

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APA (6th Edition):

Li, Q. (2016). Medical image analysis with neural network and deep learning . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/14940

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

Chicago Manual of Style (16th Edition):

Li, Qing. “Medical image analysis with neural network and deep learning .” 2016. Thesis, University of Sydney. Accessed September 24, 2020. http://hdl.handle.net/2123/14940.

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

MLA Handbook (7th Edition):

Li, Qing. “Medical image analysis with neural network and deep learning .” 2016. Web. 24 Sep 2020.

Vancouver:

Li Q. Medical image analysis with neural network and deep learning . [Internet] [Thesis]. University of Sydney; 2016. [cited 2020 Sep 24]. Available from: http://hdl.handle.net/2123/14940.

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

Council of Science Editors:

Li Q. Medical image analysis with neural network and deep learning . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/14940

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


NSYSU

10. WU, JHE-WEI. Applying Convolution Neural Network in Deep Learning to Predict on Stock Trading Strategy.

Degree: Master, Information Management, 2017, NSYSU

 The rapid increase of computing power, along with the improvement of software capabilities has made artificial intelligence a new trend. Deep learning recently becomes the… (more)

Subjects/Keywords: Convolutional Neural Network; Artificial Intelligence; Stock investment

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APA (6th Edition):

WU, J. (2017). Applying Convolution Neural Network in Deep Learning to Predict on Stock Trading Strategy. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716117-145700

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

Chicago Manual of Style (16th Edition):

WU, JHE-WEI. “Applying Convolution Neural Network in Deep Learning to Predict on Stock Trading Strategy.” 2017. Thesis, NSYSU. Accessed September 24, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716117-145700.

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

MLA Handbook (7th Edition):

WU, JHE-WEI. “Applying Convolution Neural Network in Deep Learning to Predict on Stock Trading Strategy.” 2017. Web. 24 Sep 2020.

Vancouver:

WU J. Applying Convolution Neural Network in Deep Learning to Predict on Stock Trading Strategy. [Internet] [Thesis]. NSYSU; 2017. [cited 2020 Sep 24]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716117-145700.

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

Council of Science Editors:

WU J. Applying Convolution Neural Network in Deep Learning to Predict on Stock Trading Strategy. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716117-145700

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

11. Deivasigamani R. Studies on hot deformation of as cast aluminum alloys.

Degree: Mechanical Engineering, 2014, Anna University

Aluminum alloys are widely found in various products regularly used in our daily lives, from aluminum foil for food packaging and easy open aluminum cans… (more)

Subjects/Keywords: Aluminum alloys; Artificial neural network; Mechanical Engineering

Page 1

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APA (6th Edition):

R, D. (2014). Studies on hot deformation of as cast aluminum alloys. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/16932

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

Chicago Manual of Style (16th Edition):

R, Deivasigamani. “Studies on hot deformation of as cast aluminum alloys.” 2014. Thesis, Anna University. Accessed September 24, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/16932.

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

MLA Handbook (7th Edition):

R, Deivasigamani. “Studies on hot deformation of as cast aluminum alloys.” 2014. Web. 24 Sep 2020.

Vancouver:

R D. Studies on hot deformation of as cast aluminum alloys. [Internet] [Thesis]. Anna University; 2014. [cited 2020 Sep 24]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/16932.

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

Council of Science Editors:

R D. Studies on hot deformation of as cast aluminum alloys. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/16932

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

12. Prasanna S. Intelligent multimodel content based video retrieval;.

Degree: Computer Sciences, 2009, Vels University

This research work presents artificial neural network (ANN) algorithm approach for retrieving a video, based on a query. The queries are a combination of plain… (more)

Subjects/Keywords: Computer Sciences; Artificial Neural Network; Video retrieval

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APA (6th Edition):

S, P. (2009). Intelligent multimodel content based video retrieval;. (Thesis). Vels University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/9363

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

Chicago Manual of Style (16th Edition):

S, Prasanna. “Intelligent multimodel content based video retrieval;.” 2009. Thesis, Vels University. Accessed September 24, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/9363.

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

MLA Handbook (7th Edition):

S, Prasanna. “Intelligent multimodel content based video retrieval;.” 2009. Web. 24 Sep 2020.

Vancouver:

S P. Intelligent multimodel content based video retrieval;. [Internet] [Thesis]. Vels University; 2009. [cited 2020 Sep 24]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/9363.

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. Intelligent multimodel content based video retrieval;. [Thesis]. Vels University; 2009. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/9363

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


Anna University

13. Samson S. Groundwater quality characterization using GIS and artificial neural network, in Namakkal district, "Tamilnadu".

Degree: Civil Engineering, 2013, Anna University

Water is the precious and the most essential resource that is required for the very existence of life. The largest available source of fresh water… (more)

Subjects/Keywords: Namakkal; Ground water; Artificial neural network

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APA (6th Edition):

S, S. (2013). Groundwater quality characterization using GIS and artificial neural network, in Namakkal district, "Tamilnadu". (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/10079

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

Chicago Manual of Style (16th Edition):

S, Samson. “Groundwater quality characterization using GIS and artificial neural network, in Namakkal district, "Tamilnadu".” 2013. Thesis, Anna University. Accessed September 24, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/10079.

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

MLA Handbook (7th Edition):

S, Samson. “Groundwater quality characterization using GIS and artificial neural network, in Namakkal district, "Tamilnadu".” 2013. Web. 24 Sep 2020.

Vancouver:

S S. Groundwater quality characterization using GIS and artificial neural network, in Namakkal district, "Tamilnadu". [Internet] [Thesis]. Anna University; 2013. [cited 2020 Sep 24]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/10079.

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

Council of Science Editors:

S S. Groundwater quality characterization using GIS and artificial neural network, in Namakkal district, "Tamilnadu". [Thesis]. Anna University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/10079

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


Anna University

14. Prabu S. Integration of GIS and artificial neural networks to map the landslide susceptibility in Nilgiris district.

Degree: Civil Engineering, 2013, Anna University

The term landslide includes a wide range of ground movement, such as slides, falls, flows etc. mainly based on gravity with the aid of many… (more)

Subjects/Keywords: Artificial neural network; Civil Engineering; GIS

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APA (6th Edition):

S, P. (2013). Integration of GIS and artificial neural networks to map the landslide susceptibility in Nilgiris district. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/10083

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

Chicago Manual of Style (16th Edition):

S, Prabu. “Integration of GIS and artificial neural networks to map the landslide susceptibility in Nilgiris district.” 2013. Thesis, Anna University. Accessed September 24, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/10083.

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

MLA Handbook (7th Edition):

S, Prabu. “Integration of GIS and artificial neural networks to map the landslide susceptibility in Nilgiris district.” 2013. Web. 24 Sep 2020.

Vancouver:

S P. Integration of GIS and artificial neural networks to map the landslide susceptibility in Nilgiris district. [Internet] [Thesis]. Anna University; 2013. [cited 2020 Sep 24]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/10083.

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. Integration of GIS and artificial neural networks to map the landslide susceptibility in Nilgiris district. [Thesis]. Anna University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/10083

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

15. Shanmugasundaram, D. Investigations on workability and mechanical properties of fe c ni mo andfe c cr ni mo sintered low alloy steels; -.

Degree: Mechanical Properties, 2014, SASTRA University

Abstract included newline

Reference p.137-144,, List of publications given, Summary included p.162-172

Advisors/Committee Members: Chandramouli, R.

Subjects/Keywords: Alloy steels; Artificial neural network; Plasticity Theories

Page 1

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APA (6th Edition):

Shanmugasundaram, D. (2014). Investigations on workability and mechanical properties of fe c ni mo andfe c cr ni mo sintered low alloy steels; -. (Thesis). SASTRA University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/26344

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

Chicago Manual of Style (16th Edition):

Shanmugasundaram, D. “Investigations on workability and mechanical properties of fe c ni mo andfe c cr ni mo sintered low alloy steels; -.” 2014. Thesis, SASTRA University. Accessed September 24, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/26344.

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

MLA Handbook (7th Edition):

Shanmugasundaram, D. “Investigations on workability and mechanical properties of fe c ni mo andfe c cr ni mo sintered low alloy steels; -.” 2014. Web. 24 Sep 2020.

Vancouver:

Shanmugasundaram D. Investigations on workability and mechanical properties of fe c ni mo andfe c cr ni mo sintered low alloy steels; -. [Internet] [Thesis]. SASTRA University; 2014. [cited 2020 Sep 24]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/26344.

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

Council of Science Editors:

Shanmugasundaram D. Investigations on workability and mechanical properties of fe c ni mo andfe c cr ni mo sintered low alloy steels; -. [Thesis]. SASTRA University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/26344

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


University of Nairobi

16. Kioko, Francis K. Electricity load forecasting using artificial neural networks .

Degree: 2010, University of Nairobi

 Electricity load forecasting has become increasingly important for the power industry. To generate "what is reasonably required" one needs forecast the future electricity demands. However,… (more)

Subjects/Keywords: Electricity load forecasting; Artificial neural network

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APA (6th Edition):

Kioko, F. K. (2010). Electricity load forecasting using artificial neural networks . (Thesis). University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13836

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

Chicago Manual of Style (16th Edition):

Kioko, Francis K. “Electricity load forecasting using artificial neural networks .” 2010. Thesis, University of Nairobi. Accessed September 24, 2020. http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13836.

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

MLA Handbook (7th Edition):

Kioko, Francis K. “Electricity load forecasting using artificial neural networks .” 2010. Web. 24 Sep 2020.

Vancouver:

Kioko FK. Electricity load forecasting using artificial neural networks . [Internet] [Thesis]. University of Nairobi; 2010. [cited 2020 Sep 24]. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13836.

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

Council of Science Editors:

Kioko FK. Electricity load forecasting using artificial neural networks . [Thesis]. University of Nairobi; 2010. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13836

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


Universiteit Utrecht

17. Tekofsky, S. Using an Artificial Neural Network for Predicting Reaction Time Based on Physiological Data.

Degree: 2012, Universiteit Utrecht

 In this thesis findings are described in relation to the accuracy of predicting an individual’s reaction times based on his physiological variables with the use… (more)

Subjects/Keywords: ANN; artificial neural network; reaction time; physiology

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APA (6th Edition):

Tekofsky, S. (2012). Using an Artificial Neural Network for Predicting Reaction Time Based on Physiological Data. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/253424

Chicago Manual of Style (16th Edition):

Tekofsky, S. “Using an Artificial Neural Network for Predicting Reaction Time Based on Physiological Data.” 2012. Masters Thesis, Universiteit Utrecht. Accessed September 24, 2020. http://dspace.library.uu.nl:8080/handle/1874/253424.

MLA Handbook (7th Edition):

Tekofsky, S. “Using an Artificial Neural Network for Predicting Reaction Time Based on Physiological Data.” 2012. Web. 24 Sep 2020.

Vancouver:

Tekofsky S. Using an Artificial Neural Network for Predicting Reaction Time Based on Physiological Data. [Internet] [Masters thesis]. Universiteit Utrecht; 2012. [cited 2020 Sep 24]. Available from: http://dspace.library.uu.nl:8080/handle/1874/253424.

Council of Science Editors:

Tekofsky S. Using an Artificial Neural Network for Predicting Reaction Time Based on Physiological Data. [Masters Thesis]. Universiteit Utrecht; 2012. Available from: http://dspace.library.uu.nl:8080/handle/1874/253424


Humboldt State University

18. Stobb, Michael T. A dynamic neural network model of the zebrafish posterior lateral line sensorimotor pathway.

Degree: MS, Environmental Systems: Mathematical Modeling, 2012, Humboldt State University

Neural network architecture is an important area of study in Neuroscience, as the possible dynamics of a network are highly dependent on its structure. I… (more)

Subjects/Keywords: Zebrafish; Artificial neural network; Genetic algorithm

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APA (6th Edition):

Stobb, M. T. (2012). A dynamic neural network model of the zebrafish posterior lateral line sensorimotor pathway. (Masters Thesis). Humboldt State University. Retrieved from http://hdl.handle.net/2148/1277

Chicago Manual of Style (16th Edition):

Stobb, Michael T. “A dynamic neural network model of the zebrafish posterior lateral line sensorimotor pathway.” 2012. Masters Thesis, Humboldt State University. Accessed September 24, 2020. http://hdl.handle.net/2148/1277.

MLA Handbook (7th Edition):

Stobb, Michael T. “A dynamic neural network model of the zebrafish posterior lateral line sensorimotor pathway.” 2012. Web. 24 Sep 2020.

Vancouver:

Stobb MT. A dynamic neural network model of the zebrafish posterior lateral line sensorimotor pathway. [Internet] [Masters thesis]. Humboldt State University; 2012. [cited 2020 Sep 24]. Available from: http://hdl.handle.net/2148/1277.

Council of Science Editors:

Stobb MT. A dynamic neural network model of the zebrafish posterior lateral line sensorimotor pathway. [Masters Thesis]. Humboldt State University; 2012. Available from: http://hdl.handle.net/2148/1277


King Abdullah University of Science and Technology

19. AlShahrani, Mona. Towards an Efficient Artificial Neural Network Pruning and Feature Ranking Tool.

Degree: 2015, King Abdullah University of Science and Technology

Artificial Neural Networks (ANNs) are known to be among the most effective and expressive machine learning models. Their impressive abilities to learn have been reflected… (more)

Subjects/Keywords: Artificial; Prunning; Neural; Network; Feature; Ranking

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APA (6th Edition):

AlShahrani, M. (2015). Towards an Efficient Artificial Neural Network Pruning and Feature Ranking Tool. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/555862

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

Chicago Manual of Style (16th Edition):

AlShahrani, Mona. “Towards an Efficient Artificial Neural Network Pruning and Feature Ranking Tool.” 2015. Thesis, King Abdullah University of Science and Technology. Accessed September 24, 2020. http://hdl.handle.net/10754/555862.

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

MLA Handbook (7th Edition):

AlShahrani, Mona. “Towards an Efficient Artificial Neural Network Pruning and Feature Ranking Tool.” 2015. Web. 24 Sep 2020.

Vancouver:

AlShahrani M. Towards an Efficient Artificial Neural Network Pruning and Feature Ranking Tool. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2015. [cited 2020 Sep 24]. Available from: http://hdl.handle.net/10754/555862.

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

Council of Science Editors:

AlShahrani M. Towards an Efficient Artificial Neural Network Pruning and Feature Ranking Tool. [Thesis]. King Abdullah University of Science and Technology; 2015. Available from: http://hdl.handle.net/10754/555862

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


University of California – San Diego

20. Wiest, Michael. Predicting the Complexity and Progression of the Gut Microbiome Using Temporal Data and Deep Learning.

Degree: Bioengineering, 2019, University of California – San Diego

 The human microbiota exhibit a highly dynamic composition over the course of life and changes in the human gut microbiota have been associated with human… (more)

Subjects/Keywords: Artificial intelligence; Microbiology; microbiome; neural network

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APA (6th Edition):

Wiest, M. (2019). Predicting the Complexity and Progression of the Gut Microbiome Using Temporal Data and Deep Learning. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/8pt8g0bm

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

Chicago Manual of Style (16th Edition):

Wiest, Michael. “Predicting the Complexity and Progression of the Gut Microbiome Using Temporal Data and Deep Learning.” 2019. Thesis, University of California – San Diego. Accessed September 24, 2020. http://www.escholarship.org/uc/item/8pt8g0bm.

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

MLA Handbook (7th Edition):

Wiest, Michael. “Predicting the Complexity and Progression of the Gut Microbiome Using Temporal Data and Deep Learning.” 2019. Web. 24 Sep 2020.

Vancouver:

Wiest M. Predicting the Complexity and Progression of the Gut Microbiome Using Temporal Data and Deep Learning. [Internet] [Thesis]. University of California – San Diego; 2019. [cited 2020 Sep 24]. Available from: http://www.escholarship.org/uc/item/8pt8g0bm.

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

Council of Science Editors:

Wiest M. Predicting the Complexity and Progression of the Gut Microbiome Using Temporal Data and Deep Learning. [Thesis]. University of California – San Diego; 2019. Available from: http://www.escholarship.org/uc/item/8pt8g0bm

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


University of Illinois – Chicago

21. Ciccardi, Andrea. Intelligent Scheduler for Heterogeneous System on Chip.

Degree: 2019, University of Illinois – Chicago

 This thesis presents the design of an intelligent scheduler for heterogeneous systems. The quest for performances require the heterogeneity of the systems, but in the… (more)

Subjects/Keywords: Computer Architecture; Scheduler; Neural Network; Artificial Intelligence

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APA (6th Edition):

Ciccardi, A. (2019). Intelligent Scheduler for Heterogeneous System on Chip. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/23736

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

Chicago Manual of Style (16th Edition):

Ciccardi, Andrea. “Intelligent Scheduler for Heterogeneous System on Chip.” 2019. Thesis, University of Illinois – Chicago. Accessed September 24, 2020. http://hdl.handle.net/10027/23736.

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

MLA Handbook (7th Edition):

Ciccardi, Andrea. “Intelligent Scheduler for Heterogeneous System on Chip.” 2019. Web. 24 Sep 2020.

Vancouver:

Ciccardi A. Intelligent Scheduler for Heterogeneous System on Chip. [Internet] [Thesis]. University of Illinois – Chicago; 2019. [cited 2020 Sep 24]. Available from: http://hdl.handle.net/10027/23736.

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

Council of Science Editors:

Ciccardi A. Intelligent Scheduler for Heterogeneous System on Chip. [Thesis]. University of Illinois – Chicago; 2019. Available from: http://hdl.handle.net/10027/23736

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


Laurentian University

22. Zuo, Hongming. A self-learning audio player that uses a rough set and neural net hybrid approach .

Degree: 2013, Laurentian University

 A self-­‐learning Audio Player was built to learn users habits by analyzing operations the user does when listening to music. The self-­‐learning component is intended… (more)

Subjects/Keywords: self learning; Artificial Neural Network; music; NN

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APA (6th Edition):

Zuo, H. (2013). A self-learning audio player that uses a rough set and neural net hybrid approach . (Thesis). Laurentian University. Retrieved from https://zone.biblio.laurentian.ca/dspace/handle/10219/2117

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

Chicago Manual of Style (16th Edition):

Zuo, Hongming. “A self-learning audio player that uses a rough set and neural net hybrid approach .” 2013. Thesis, Laurentian University. Accessed September 24, 2020. https://zone.biblio.laurentian.ca/dspace/handle/10219/2117.

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

MLA Handbook (7th Edition):

Zuo, Hongming. “A self-learning audio player that uses a rough set and neural net hybrid approach .” 2013. Web. 24 Sep 2020.

Vancouver:

Zuo H. A self-learning audio player that uses a rough set and neural net hybrid approach . [Internet] [Thesis]. Laurentian University; 2013. [cited 2020 Sep 24]. Available from: https://zone.biblio.laurentian.ca/dspace/handle/10219/2117.

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

Council of Science Editors:

Zuo H. A self-learning audio player that uses a rough set and neural net hybrid approach . [Thesis]. Laurentian University; 2013. Available from: https://zone.biblio.laurentian.ca/dspace/handle/10219/2117

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


Kansas State University

23. Datta, Pallab Kumar. An artificial neural network approach for short-term wind speed forecast.

Degree: MS, Department of Electrical and Computer Engineering, 2018, Kansas State University

 Electricity generation capacity from different renewable sources has been significantly growing worldwide in recent years, specially wind power. Fast dispatch of wind power provides flexibility… (more)

Subjects/Keywords: Artificial neural network; Wind speed forecast

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APA (6th Edition):

Datta, P. K. (2018). An artificial neural network approach for short-term wind speed forecast. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/38945

Chicago Manual of Style (16th Edition):

Datta, Pallab Kumar. “An artificial neural network approach for short-term wind speed forecast.” 2018. Masters Thesis, Kansas State University. Accessed September 24, 2020. http://hdl.handle.net/2097/38945.

MLA Handbook (7th Edition):

Datta, Pallab Kumar. “An artificial neural network approach for short-term wind speed forecast.” 2018. Web. 24 Sep 2020.

Vancouver:

Datta PK. An artificial neural network approach for short-term wind speed forecast. [Internet] [Masters thesis]. Kansas State University; 2018. [cited 2020 Sep 24]. Available from: http://hdl.handle.net/2097/38945.

Council of Science Editors:

Datta PK. An artificial neural network approach for short-term wind speed forecast. [Masters Thesis]. Kansas State University; 2018. Available from: http://hdl.handle.net/2097/38945

24. Maya L Pai; Dr. A N Balchand; Dr. K V Pramod. ANN based Data Mining Technique to Achieve Improved Accuracy to Predict ISMR from Ocean –Atmosphere State Variables.

Degree: 2016, Cochin University of Science and Technology

ANN based long range forecast of Indian summer monsoon rainfall for the hydrological regions of India using ocean and atmosphere state parameters with improved accuracy,Trend analysis of SST, sub surface temperature of Indian Ocean and that of ISMR. 3. Prediction of extreme rainfall events using ANN.

Subjects/Keywords: Neural Network; Artificial Neural Network; Human and Artificial neuron; Indian Monsoons; Atmosphere Ocean variability

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APA (6th Edition):

Pramod, M. L. P. D. A. N. B. D. K. V. (2016). ANN based Data Mining Technique to Achieve Improved Accuracy to Predict ISMR from Ocean –Atmosphere State Variables. (Thesis). Cochin University of Science and Technology. Retrieved from http://dyuthi.cusat.ac.in/purl/5152

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

Chicago Manual of Style (16th Edition):

Pramod, Maya L Pai; Dr. A N Balchand; Dr. K V. “ANN based Data Mining Technique to Achieve Improved Accuracy to Predict ISMR from Ocean –Atmosphere State Variables.” 2016. Thesis, Cochin University of Science and Technology. Accessed September 24, 2020. http://dyuthi.cusat.ac.in/purl/5152.

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

MLA Handbook (7th Edition):

Pramod, Maya L Pai; Dr. A N Balchand; Dr. K V. “ANN based Data Mining Technique to Achieve Improved Accuracy to Predict ISMR from Ocean –Atmosphere State Variables.” 2016. Web. 24 Sep 2020.

Vancouver:

Pramod MLPDANBDKV. ANN based Data Mining Technique to Achieve Improved Accuracy to Predict ISMR from Ocean –Atmosphere State Variables. [Internet] [Thesis]. Cochin University of Science and Technology; 2016. [cited 2020 Sep 24]. Available from: http://dyuthi.cusat.ac.in/purl/5152.

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

Council of Science Editors:

Pramod MLPDANBDKV. ANN based Data Mining Technique to Achieve Improved Accuracy to Predict ISMR from Ocean –Atmosphere State Variables. [Thesis]. Cochin University of Science and Technology; 2016. Available from: http://dyuthi.cusat.ac.in/purl/5152

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

25. Pinto, Adriano Bessa. Controlo de um robô autónomo através de redes neuronais.

Degree: 2013, Instituto Politécnico do Porto

Neste trabalho pretende-se introduzir os conceitos associados às redes neuronais e a sua aplicação no controlo de sistemas, neste caso na área da robótica autónoma.… (more)

Subjects/Keywords: Rede neuronal artificial; AGV; MATLAB; Android; Artificial neural network

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APA (6th Edition):

Pinto, A. B. (2013). Controlo de um robô autónomo através de redes neuronais. (Thesis). Instituto Politécnico do Porto. Retrieved from https://www.rcaap.pt/detail.jsp?id=oai:recipp.ipp.pt:10400.22/4612

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

Chicago Manual of Style (16th Edition):

Pinto, Adriano Bessa. “Controlo de um robô autónomo através de redes neuronais.” 2013. Thesis, Instituto Politécnico do Porto. Accessed September 24, 2020. https://www.rcaap.pt/detail.jsp?id=oai:recipp.ipp.pt:10400.22/4612.

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

MLA Handbook (7th Edition):

Pinto, Adriano Bessa. “Controlo de um robô autónomo através de redes neuronais.” 2013. Web. 24 Sep 2020.

Vancouver:

Pinto AB. Controlo de um robô autónomo através de redes neuronais. [Internet] [Thesis]. Instituto Politécnico do Porto; 2013. [cited 2020 Sep 24]. Available from: https://www.rcaap.pt/detail.jsp?id=oai:recipp.ipp.pt:10400.22/4612.

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

Council of Science Editors:

Pinto AB. Controlo de um robô autónomo através de redes neuronais. [Thesis]. Instituto Politécnico do Porto; 2013. Available from: https://www.rcaap.pt/detail.jsp?id=oai:recipp.ipp.pt:10400.22/4612

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


Penn State University

26. McCandless, Tyler. Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction.

Degree: 2015, Penn State University

 The world’s energy system will increasingly depend upon renewable energy sources, including solar power, due to the limitation of fossil fuel resources and their influence… (more)

Subjects/Keywords: Solar irradiance; artificial intelligence; artificial neural network; solar power; regime-dependent

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APA (6th Edition):

McCandless, T. (2015). Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/26831

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

Chicago Manual of Style (16th Edition):

McCandless, Tyler. “Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction.” 2015. Thesis, Penn State University. Accessed September 24, 2020. https://submit-etda.libraries.psu.edu/catalog/26831.

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

MLA Handbook (7th Edition):

McCandless, Tyler. “Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction.” 2015. Web. 24 Sep 2020.

Vancouver:

McCandless T. Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction. [Internet] [Thesis]. Penn State University; 2015. [cited 2020 Sep 24]. Available from: https://submit-etda.libraries.psu.edu/catalog/26831.

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

Council of Science Editors:

McCandless T. Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction. [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/26831

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

27. Luiz Henrique Gomes Popoff. Controle preditivo neural aplicado à processos petroquímicos.

Degree: 2009, Universidade Federal do Rio Grande do Norte

 A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um… (more)

Subjects/Keywords: Controle preditivo; Controle avançado; Rede neural artificial; ENGENHARIAS; Advanced control; Artificial neural network; Predictive control

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APA (6th Edition):

Popoff, L. H. G. (2009). Controle preditivo neural aplicado à processos petroquímicos. (Thesis). Universidade Federal do Rio Grande do Norte. Retrieved from http://bdtd.bczm.ufrn.br/tedesimplificado//tde_busca/arquivo.php?codArquivo=3698

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

Chicago Manual of Style (16th Edition):

Popoff, Luiz Henrique Gomes. “Controle preditivo neural aplicado à processos petroquímicos.” 2009. Thesis, Universidade Federal do Rio Grande do Norte. Accessed September 24, 2020. http://bdtd.bczm.ufrn.br/tedesimplificado//tde_busca/arquivo.php?codArquivo=3698.

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

MLA Handbook (7th Edition):

Popoff, Luiz Henrique Gomes. “Controle preditivo neural aplicado à processos petroquímicos.” 2009. Web. 24 Sep 2020.

Vancouver:

Popoff LHG. Controle preditivo neural aplicado à processos petroquímicos. [Internet] [Thesis]. Universidade Federal do Rio Grande do Norte; 2009. [cited 2020 Sep 24]. Available from: http://bdtd.bczm.ufrn.br/tedesimplificado//tde_busca/arquivo.php?codArquivo=3698.

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

Council of Science Editors:

Popoff LHG. Controle preditivo neural aplicado à processos petroquímicos. [Thesis]. Universidade Federal do Rio Grande do Norte; 2009. Available from: http://bdtd.bczm.ufrn.br/tedesimplificado//tde_busca/arquivo.php?codArquivo=3698

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

28. Ramalho, José Pinto. Oxicorte: estudo da transferência de calor e modelamento por redes neurais artificiais de variáveis do processo.

Degree: PhD, Engenharia Metalúrgica e de Materiais, 2008, University of São Paulo

O oxicorte produz superfícies que variam entre um padrão semelhante à usinagem até outro em que o corte é praticamente sem qualidade. Além das condições… (more)

Subjects/Keywords: Artificial Neural Network; Heat transfer; Modelamento; Modeling; Oxicorte; Oxicutting; Rede Neural Artificial; Transferência de calor

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

APA (6th Edition):

Ramalho, J. P. (2008). Oxicorte: estudo da transferência de calor e modelamento por redes neurais artificiais de variáveis do processo. (Doctoral Dissertation). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/3/3133/tde-30092008-150619/ ;

Chicago Manual of Style (16th Edition):

Ramalho, José Pinto. “Oxicorte: estudo da transferência de calor e modelamento por redes neurais artificiais de variáveis do processo.” 2008. Doctoral Dissertation, University of São Paulo. Accessed September 24, 2020. http://www.teses.usp.br/teses/disponiveis/3/3133/tde-30092008-150619/ ;.

MLA Handbook (7th Edition):

Ramalho, José Pinto. “Oxicorte: estudo da transferência de calor e modelamento por redes neurais artificiais de variáveis do processo.” 2008. Web. 24 Sep 2020.

Vancouver:

Ramalho JP. Oxicorte: estudo da transferência de calor e modelamento por redes neurais artificiais de variáveis do processo. [Internet] [Doctoral dissertation]. University of São Paulo; 2008. [cited 2020 Sep 24]. Available from: http://www.teses.usp.br/teses/disponiveis/3/3133/tde-30092008-150619/ ;.

Council of Science Editors:

Ramalho JP. Oxicorte: estudo da transferência de calor e modelamento por redes neurais artificiais de variáveis do processo. [Doctoral Dissertation]. University of São Paulo; 2008. Available from: http://www.teses.usp.br/teses/disponiveis/3/3133/tde-30092008-150619/ ;


Universidade do Rio Grande do Norte

29. Araújo, Eduardo Henrique Silveira de. Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR .

Degree: 2013, Universidade do Rio Grande do Norte

 This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary… (more)

Subjects/Keywords: Porosidade. GPR. Sistema inteligente. Rede neural artificial; Porosity. GPR. Intelligent system. Artificial neural network

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Araújo, E. H. S. d. (2013). Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR . (Thesis). Universidade do Rio Grande do Norte. Retrieved from http://repositorio.ufrn.br/handle/123456789/13023

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

Chicago Manual of Style (16th Edition):

Araújo, Eduardo Henrique Silveira de. “Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR .” 2013. Thesis, Universidade do Rio Grande do Norte. Accessed September 24, 2020. http://repositorio.ufrn.br/handle/123456789/13023.

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

MLA Handbook (7th Edition):

Araújo, Eduardo Henrique Silveira de. “Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR .” 2013. Web. 24 Sep 2020.

Vancouver:

Araújo EHSd. Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR . [Internet] [Thesis]. Universidade do Rio Grande do Norte; 2013. [cited 2020 Sep 24]. Available from: http://repositorio.ufrn.br/handle/123456789/13023.

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

Council of Science Editors:

Araújo EHSd. Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR . [Thesis]. Universidade do Rio Grande do Norte; 2013. Available from: http://repositorio.ufrn.br/handle/123456789/13023

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


Universidade do Rio Grande do Norte

30. Araújo, Eduardo Henrique Silveira de. Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR .

Degree: 2013, Universidade do Rio Grande do Norte

 This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary… (more)

Subjects/Keywords: Porosidade. GPR. Sistema inteligente. Rede neural artificial; Porosity. GPR. Intelligent system. Artificial neural network

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Araújo, E. H. S. d. (2013). Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR . (Doctoral Dissertation). Universidade do Rio Grande do Norte. Retrieved from http://repositorio.ufrn.br/handle/123456789/13023

Chicago Manual of Style (16th Edition):

Araújo, Eduardo Henrique Silveira de. “Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR .” 2013. Doctoral Dissertation, Universidade do Rio Grande do Norte. Accessed September 24, 2020. http://repositorio.ufrn.br/handle/123456789/13023.

MLA Handbook (7th Edition):

Araújo, Eduardo Henrique Silveira de. “Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR .” 2013. Web. 24 Sep 2020.

Vancouver:

Araújo EHSd. Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR . [Internet] [Doctoral dissertation]. Universidade do Rio Grande do Norte; 2013. [cited 2020 Sep 24]. Available from: http://repositorio.ufrn.br/handle/123456789/13023.

Council of Science Editors:

Araújo EHSd. Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR . [Doctoral Dissertation]. Universidade do Rio Grande do Norte; 2013. Available from: http://repositorio.ufrn.br/handle/123456789/13023

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