Knowledge representation in electrical insulation diagnosis

Gao Ning Gao Ning,Zhu Deheng Zhu Deheng,Yang Li Yang Li,Yan Zhang Yan Zhang

doi:10.1109/icpst.1998.728932

Knowledge representation in electrical insulation diagnosis

Gao Ning Gao Ning, Zhu Deheng Zhu Deheng + Show 2 more

https://doi.org/10.1109/icpst.1998.728932

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Publication Date: Aug 18, 1998

Affiliation: Tsinghua University, Xi'an Jiaotong University

#Artificial Neural Network Representation #Artificial Neural Network + Show 8 more

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Abstract

An artificial neural network (ANN) representation method is presented and discussed in this paper. ANN representation of symbolic and numeric knowledge is realized by the improved backpropagation (BP) algorithm. The method of management and organization of ANN representation is presented also. The problem that numeric knowledge is difficult to be represented is effectively solved by the network. After learning, the threshold values and weights of ANN are ensured and the diagnostic knowledge is learned. The practical examples are used to check the diagnostic results. It is shown that the ANN representation method is effective.

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