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...
保存先:
| 主要な著者: | , , , |
|---|---|
| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Taylor & Francis
2011
|
| オンライン･アクセス: | 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 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
インターネット
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