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| 摘要: |
| 将基于粗糙集理论的模糊神经网络，应用于变压器故障诊断中，充分利用粗糙集理论对知识的约简能力模糊神经网络优良的分类能力，首先利用粗糙集方法对原始数据进行约简，形成精简的规则集，以此基础构建的模糊神经网络结构完全是由粗糙集最终约简规则决定的，具有良好的拓扑结构，网络规模大大减少，学习速度大为提高，而且保持了网络较好的分类能力。 |
| 关键词: 粗糙集 模糊神经网络 变压器 故障诊断 电力变压器 人工智能 |
| DOI： |
| 分类号:TM41 TP18 |
| 基金项目: |
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| Transformer fault diagnosis based on rough set theory and neural fuzzy network |
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YU Xiao-dong SUN Ying ZANG Hong-zhi
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| Abstract: |
| The fuzzy neural network which based on RS(Rough Set)theory is applied in transformer fault diagnosis.It fully develops the reduction ability of RS theory and the classification ability of fuzzy neural network.Using RS theory,the original data reduction is performed first to form a simple rule collection,based on which the structure of fuzzy neural network is then completely determined.It has a better topological structure with greatly reduced network scale and greatly improved learning speed,while keeps the good classification ability of network. |
| Key words: transformer,fault diagnosis,rough set,fuzzy neural network |
