Comparative analysis of probabilistic neural network, radial basis function, and feed-forward neural network for fault classification in power distribution systems
This article presents a classification methodology based on probabilistic neural networks. To automatically select the training data and obtain the performance evaluation results, the “K-fold” cross-validation method is used. Then, the probabilistic neural network is compared with the feed-forward n...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis
2011
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Online Access: | http://psasir.upm.edu.my/id/eprint/23169/1/Comparative%20analysis%20of%20probabilistic%20neural%20network%2C%20radial%20basis%20function%2C%20and%20feed-forward%20neural%20network%20for%20fault%20classification%20in%20power%20distribution%20systems.pdf http://psasir.upm.edu.my/id/eprint/23169/ http://www.tandfonline.com/doi/abs/10.1080/15325008.2011.615802 |
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Institution: | Universiti Putra Malaysia |
Language: | English |
Internet
http://psasir.upm.edu.my/id/eprint/23169/1/Comparative%20analysis%20of%20probabilistic%20neural%20network%2C%20radial%20basis%20function%2C%20and%20feed-forward%20neural%20network%20for%20fault%20classification%20in%20power%20distribution%20systems.pdfhttp://psasir.upm.edu.my/id/eprint/23169/
http://www.tandfonline.com/doi/abs/10.1080/15325008.2011.615802