Application of Fuzyy Set Theory and Neural Network in Analysis on Metal Oxide Varistor’s Voltage-Current Characteristic

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Application of Fuzyy Set Theory and Neural Network in Analysis on Metal Oxide Varistor’s Voltage-Current Characteristic

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- Application of Fuzyy Set Theory and Neural Network in Analysis on Metal Oxide Varistor’s Voltage-Current Characteristic
- High VoltageApparatus Issue 2, Pages: 6-9+13(1998)
- 作者机构：
  
  1. 华中理工大学
  2. 华中理工大学武汉430074
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP183
- Published：1998
- 稿件说明：
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[1]周龙,文远芳,詹琼华,招誉颐.模糊集理论和神经网络在氧化锌阀片伏安特性分析中的应用[J].高压电器,1998(02):6-9+13.

Application of Fuzyy Set Theory and Neural Network in Analysis on Metal Oxide Varistor’s Voltage-Current Characteristic[J]. High voltageapparatus, 1998, (2): 6-9+13.
[1]周龙,文远芳,詹琼华,招誉颐.模糊集理论和神经网络在氧化锌阀片伏安特性分析中的应用[J].高压电器,1998(02):6-9+13. DOI：

Application of Fuzyy Set Theory and Neural Network in Analysis on Metal Oxide Varistor’s Voltage-Current Characteristic[J]. High voltageapparatus, 1998, (2): 6-9+13. DOI：

摘要

提出了根据氧化锌阀片（MOV）伏安特性进行筛选组合中的模糊聚类方法

并利用神经网络对它进行拟合。最后用实例说明了这种处理方法的有效性。

Abstract

This paper discusses a method of the fuzzy clustering to select the Metal -Oxide Varistors（MOV） based on their voltage current characteristic. And the neural network is used to simulate the MOV’s voltage -current characteristic. Finally

the method is proved to be effective by an example.

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