A fault line selection method for small current grounding system
In view of problem that fault line selection method for small current grounding system is difficult to be suitable for different grounding modes, the paper proposed a fault line selection method for small current grounding system based on RBF neural network optimized by particle swarm. The method us...
| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Industry and Mine Automation
2013-10-01
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| Series: | Gong-kuang zidonghua |
| Subjects: | |
| Online Access: | http://www.gkzdh.cn/article/doi/10.7526/j.issn.1671-251X.2013.10.020 |
| _version_ | 1797868637576495104 |
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| author | SHI Dan SHAO Ru-ping XU Ju |
| author_facet | SHI Dan SHAO Ru-ping XU Ju |
| author_sort | SHI Dan |
| collection | DOAJ |
| description | In view of problem that fault line selection method for small current grounding system is difficult to be suitable for different grounding modes, the paper proposed a fault line selection method for small current grounding system based on RBF neural network optimized by particle swarm. The method uses particle swarm optimization algorithm to optimize RBF neural network, takes parameters confirmed by the RBF neural network as particles of the particle swarm optimization algorithm. The simulation result shows that the method has high convergence efficiency, small sum of square of error, high accuracy of line selection, high sensitivity and a certain feasibility. |
| first_indexed | 2024-04-09T23:59:03Z |
| format | Article |
| id | doaj.art-6ac4b30e4336497d81faf605f17f35b1 |
| institution | Directory Open Access Journal |
| issn | 1671-251X |
| language | zho |
| last_indexed | 2024-04-09T23:59:03Z |
| publishDate | 2013-10-01 |
| publisher | Editorial Department of Industry and Mine Automation |
| record_format | Article |
| series | Gong-kuang zidonghua |
| spelling | doaj.art-6ac4b30e4336497d81faf605f17f35b12023-03-17T01:53:00ZzhoEditorial Department of Industry and Mine AutomationGong-kuang zidonghua1671-251X2013-10-013910778010.7526/j.issn.1671-251X.2013.10.020A fault line selection method for small current grounding systemSHI DanSHAO Ru-pingXU JuIn view of problem that fault line selection method for small current grounding system is difficult to be suitable for different grounding modes, the paper proposed a fault line selection method for small current grounding system based on RBF neural network optimized by particle swarm. The method uses particle swarm optimization algorithm to optimize RBF neural network, takes parameters confirmed by the RBF neural network as particles of the particle swarm optimization algorithm. The simulation result shows that the method has high convergence efficiency, small sum of square of error, high accuracy of line selection, high sensitivity and a certain feasibility.http://www.gkzdh.cn/article/doi/10.7526/j.issn.1671-251X.2013.10.020small current grounding systemfault line selectionparticle swarm optimizationrbf neural network |
| spellingShingle | SHI Dan SHAO Ru-ping XU Ju A fault line selection method for small current grounding system Gong-kuang zidonghua small current grounding system fault line selection particle swarm optimization rbf neural network |
| title | A fault line selection method for small current grounding system |
| title_full | A fault line selection method for small current grounding system |
| title_fullStr | A fault line selection method for small current grounding system |
| title_full_unstemmed | A fault line selection method for small current grounding system |
| title_short | A fault line selection method for small current grounding system |
| title_sort | fault line selection method for small current grounding system |
| topic | small current grounding system fault line selection particle swarm optimization rbf neural network |
| url | http://www.gkzdh.cn/article/doi/10.7526/j.issn.1671-251X.2013.10.020 |
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