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You searched for subject:(Artificial neural network). Showing records 1 – 30 of 782 total matches.

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University of Nairobi

1. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Onyango PO. Maize crop yield prediction through reinforcement learning, artificial neural network and alert messages generation . [Internet] [Thesis]. University of Nairobi; 2012. [cited 2019 Sep 15]. 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


Penn State University

2. Chidambaram, Prasanna. DEVELOPMENT AND TESTING OF AN ARTIFICIAL NEURAL NETWORK BASED.

Degree: PhD, Petroleum and Natural Gas Engineering, 2009, Penn State University

 History matching is one of the more critical steps in the reservoir performance predictions. It is during this step the reservoir parameters used in the… (more)

Subjects/Keywords: Artificial neural network; History matching

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APA (6th Edition):

Chidambaram, P. (2009). DEVELOPMENT AND TESTING OF AN ARTIFICIAL NEURAL NETWORK BASED. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9336

Chicago Manual of Style (16th Edition):

Chidambaram, Prasanna. “DEVELOPMENT AND TESTING OF AN ARTIFICIAL NEURAL NETWORK BASED.” 2009. Doctoral Dissertation, Penn State University. Accessed September 15, 2019. https://etda.libraries.psu.edu/catalog/9336.

MLA Handbook (7th Edition):

Chidambaram, Prasanna. “DEVELOPMENT AND TESTING OF AN ARTIFICIAL NEURAL NETWORK BASED.” 2009. Web. 15 Sep 2019.

Vancouver:

Chidambaram P. DEVELOPMENT AND TESTING OF AN ARTIFICIAL NEURAL NETWORK BASED. [Internet] [Doctoral dissertation]. Penn State University; 2009. [cited 2019 Sep 15]. Available from: https://etda.libraries.psu.edu/catalog/9336.

Council of Science Editors:

Chidambaram P. DEVELOPMENT AND TESTING OF AN ARTIFICIAL NEURAL NETWORK BASED. [Doctoral Dissertation]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9336


Kansas State University

3. 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 15, 2019. 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. 15 Sep 2019.

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 2019 Sep 15]. 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


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 15, 2019. 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. 15 Sep 2019.

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 2019 Sep 15]. 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


Penn State University

5. Ma, Jaehyun. DESIGN OF AN EFFECTIVE WATER-ALTERNATING-GAS(WAG) INJECTION PROCESS USING ARTIFICIAL EXPERT SYSTEMS.

Degree: MS, Petroleum and Natural Gas Engineering, 2010, Penn State University

 Numerical reservoir simulators are commonly used to simulate the water-alternating-gas process for hydrocarbon reservoir. However, a reservoir simulation study can only provide information about the… (more)

Subjects/Keywords: artificial neural network; WAG; inverse network

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APA (6th Edition):

Ma, J. (2010). DESIGN OF AN EFFECTIVE WATER-ALTERNATING-GAS(WAG) INJECTION PROCESS USING ARTIFICIAL EXPERT SYSTEMS. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/10786

Chicago Manual of Style (16th Edition):

Ma, Jaehyun. “DESIGN OF AN EFFECTIVE WATER-ALTERNATING-GAS(WAG) INJECTION PROCESS USING ARTIFICIAL EXPERT SYSTEMS.” 2010. Masters Thesis, Penn State University. Accessed September 15, 2019. https://etda.libraries.psu.edu/catalog/10786.

MLA Handbook (7th Edition):

Ma, Jaehyun. “DESIGN OF AN EFFECTIVE WATER-ALTERNATING-GAS(WAG) INJECTION PROCESS USING ARTIFICIAL EXPERT SYSTEMS.” 2010. Web. 15 Sep 2019.

Vancouver:

Ma J. DESIGN OF AN EFFECTIVE WATER-ALTERNATING-GAS(WAG) INJECTION PROCESS USING ARTIFICIAL EXPERT SYSTEMS. [Internet] [Masters thesis]. Penn State University; 2010. [cited 2019 Sep 15]. Available from: https://etda.libraries.psu.edu/catalog/10786.

Council of Science Editors:

Ma J. DESIGN OF AN EFFECTIVE WATER-ALTERNATING-GAS(WAG) INJECTION PROCESS USING ARTIFICIAL EXPERT SYSTEMS. [Masters Thesis]. Penn State University; 2010. Available from: https://etda.libraries.psu.edu/catalog/10786

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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Almeida MCd. Sistema tutor monitorado por rede neural artificial. [Internet] [Thesis]. Federal University of Uberlândia; 2006. [cited 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Muthukumaran S. Investigations on neural network models for short term load forecasting; -. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Sep 15]. 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


University of Georgia

8. Li, Bin. Spatial interpolation of weather variables using artificial neural networks.

Degree: MS, Artificial Intelligence, 2002, University of Georgia

 Crop growth simulation models use weather data such as temperature, solar radiation, and rainfall to simulate crop development and yield. The crop models are often… (more)

Subjects/Keywords: Artificial neural network

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APA (6th Edition):

Li, B. (2002). Spatial interpolation of weather variables using artificial neural networks. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/li_bin_200208_ms

Chicago Manual of Style (16th Edition):

Li, Bin. “Spatial interpolation of weather variables using artificial neural networks.” 2002. Masters Thesis, University of Georgia. Accessed September 15, 2019. http://purl.galileo.usg.edu/uga_etd/li_bin_200208_ms.

MLA Handbook (7th Edition):

Li, Bin. “Spatial interpolation of weather variables using artificial neural networks.” 2002. Web. 15 Sep 2019.

Vancouver:

Li B. Spatial interpolation of weather variables using artificial neural networks. [Internet] [Masters thesis]. University of Georgia; 2002. [cited 2019 Sep 15]. Available from: http://purl.galileo.usg.edu/uga_etd/li_bin_200208_ms.

Council of Science Editors:

Li B. Spatial interpolation of weather variables using artificial neural networks. [Masters Thesis]. University of Georgia; 2002. Available from: http://purl.galileo.usg.edu/uga_etd/li_bin_200208_ms


University of Georgia

9. Liu, Lin. Prediction of poultry deep body temperatures using artificial neural networks.

Degree: MS, Artificial Intelligence, 2002, University of Georgia

 To understand the relationships among ambient temperature (AT), relative humidity (RH) and broiler deep body temperature (DBT), controlled experiments were conducted for different RH (50… (more)

Subjects/Keywords: Artificial Neural Network

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APA (6th Edition):

Liu, L. (2002). Prediction of poultry deep body temperatures using artificial neural networks. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/liu_lin_200212_ms

Chicago Manual of Style (16th Edition):

Liu, Lin. “Prediction of poultry deep body temperatures using artificial neural networks.” 2002. Masters Thesis, University of Georgia. Accessed September 15, 2019. http://purl.galileo.usg.edu/uga_etd/liu_lin_200212_ms.

MLA Handbook (7th Edition):

Liu, Lin. “Prediction of poultry deep body temperatures using artificial neural networks.” 2002. Web. 15 Sep 2019.

Vancouver:

Liu L. Prediction of poultry deep body temperatures using artificial neural networks. [Internet] [Masters thesis]. University of Georgia; 2002. [cited 2019 Sep 15]. Available from: http://purl.galileo.usg.edu/uga_etd/liu_lin_200212_ms.

Council of Science Editors:

Liu L. Prediction of poultry deep body temperatures using artificial neural networks. [Masters Thesis]. University of Georgia; 2002. Available from: http://purl.galileo.usg.edu/uga_etd/liu_lin_200212_ms


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 15, 2019. 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. 15 Sep 2019.

Vancouver:

WU J. Applying Convolution Neural Network in Deep Learning to Predict on Stock Trading Strategy. [Internet] [Thesis]. NSYSU; 2017. [cited 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

R D. Studies on hot deformation of as cast aluminum alloys. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

S P. Intelligent multimodel content based video retrieval;. [Internet] [Thesis]. Vels University; 2009. [cited 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

S S. Groundwater quality characterization using GIS and artificial neural network, in Namakkal district, "Tamilnadu". [Internet] [Thesis]. Anna University; 2013. [cited 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

S P. Integration of GIS and artificial neural networks to map the landslide susceptibility in Nilgiris district. [Internet] [Thesis]. Anna University; 2013. [cited 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

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 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Kioko FK. Electricity load forecasting using artificial neural networks . [Internet] [Thesis]. University of Nairobi; 2010. [cited 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Tekofsky S. Using an Artificial Neural Network for Predicting Reaction Time Based on Physiological Data. [Internet] [Masters thesis]. Universiteit Utrecht; 2012. [cited 2019 Sep 15]. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Stobb MT. A dynamic neural network model of the zebrafish posterior lateral line sensorimotor pathway. [Internet] [Masters thesis]. Humboldt State University; 2012. [cited 2019 Sep 15]. 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


Laurentian University

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

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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Zuo H. A self-learning audio player that uses a rough set and neural net hybrid approach . [Internet] [Thesis]. Laurentian University; 2013. [cited 2019 Sep 15]. 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


University of Sydney

20. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Li Q. Medical image analysis with neural network and deep learning . [Internet] [Thesis]. University of Sydney; 2016. [cited 2019 Sep 15]. 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


King Abdullah University of Science and Technology

21. 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 15, 2019. 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. 15 Sep 2019.

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 2019 Sep 15]. 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


Kansas State University

22. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Datta PK. An artificial neural network approach for short-term wind speed forecast. [Internet] [Masters thesis]. Kansas State University; 2018. [cited 2019 Sep 15]. 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


University of California – San Diego

23. 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 15, 2019. 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. 15 Sep 2019.

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 2019 Sep 15]. 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


Laurentian University

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

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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Zuo H. A self-learning audio player that uses a rough set and neural net hybrid approach . [Internet] [Thesis]. Laurentian University; 2013. [cited 2019 Sep 15]. 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

25. 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 15, 2019. 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. 15 Sep 2019.

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 2019 Sep 15]. 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


Penn State University

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

Degree: PhD, Meteorology, 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. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26831

Chicago Manual of Style (16th Edition):

McCandless, Tyler. “Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction.” 2015. Doctoral Dissertation, Penn State University. Accessed September 15, 2019. https://etda.libraries.psu.edu/catalog/26831.

MLA Handbook (7th Edition):

McCandless, Tyler. “Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction.” 2015. Web. 15 Sep 2019.

Vancouver:

McCandless T. Artificial Intelligence Techniques for Short-range Solar Irradiance Prediction. [Internet] [Doctoral dissertation]. Penn State University; 2015. [cited 2019 Sep 15]. Available from: https://etda.libraries.psu.edu/catalog/26831.

Council of Science Editors:

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

27. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Pinto AB. Controlo de um robô autónomo através de redes neuronais. [Internet] [Thesis]. Instituto Politécnico do Porto; 2013. [cited 2019 Sep 15]. 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

28. 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 15, 2019. 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. 15 Sep 2019.

Vancouver:

Popoff LHG. Controle preditivo neural aplicado à processos petroquímicos. [Internet] [Thesis]. Universidade Federal do Rio Grande do Norte; 2009. [cited 2019 Sep 15]. 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

29. 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 15, 2019. 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. 15 Sep 2019.

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 2019 Sep 15]. 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

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

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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 15, 2019. 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. 15 Sep 2019.

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 2019 Sep 15]. 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

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