| 基于粗糙集和IRBF的配电网故障诊断系统 |
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| 引用本文： | 程拥军,陈小丽.基于粗糙集和IRBF的配电网故障诊断系统[J].计算机测量与控制,2011,19(5). |
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| 作者姓名： | 程拥军 陈小丽 |
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| 作者单位： | 湖南工业大学计算机与通信学院,湖南,株洲,412000 |
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| 基金项目： | 湖北省自然科学基金(H72342067T) |
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| 摘 要： | 为了改进人工智能方法在配电网故障诊断系统中的应用,给出了基于粗糙集理论的IRBF神经网络的模型结构,然后利用训练好的神经网络对配电网进行故障诊断;采用VC++语言开发工具,调用Matlab神经网络工具箱建立了一个简化的故障诊断系统,并通过配电网实例验证了方法的正确性;实践证明不但提高了配电网故障诊断的容错性,使故障诊断变得更加准确有效,而且减少了神经网络样本数据,大大地减少了故障诊断过程的时间。
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| 关 键 词： | 配电网 故障诊断 粗糙集 IRBF |
Research of Rough Set-RBF Neural Network Fault Diagnosis Method about Distribution Network |
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| Cheng Yongjun,Chen Xiaoli.Research of Rough Set-RBF Neural Network Fault Diagnosis Method about Distribution Network[J].Computer Measurement & Control,2011,19(5). |
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| Authors: | Cheng Yongjun Chen Xiaoli |
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| Affiliation: | Cheng Yongjun,Chen Xiaoli(Hunan University of Technology,Zhuzhou 412000,China) |
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| Abstract: | In order to improve artificial intelligence methods in fault diagnosis system of the distribution network are given RBF neural network model structure based on rough set theory,and then use the trained neural network for the distribution network fault diagnosis.Using Visual C++ language development tools,called Matlab neural network toolbox to establish a simplified fault diagnosis system,and through examples to verify the method.It has proved that not only improve the distribution network fault diagnosis a... |
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| Keywords: | distribution network fault diagnosis rough sets immune radial basis function |
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