The application of the data mining based on adaptive immune algorithm for power transformer, fault diagnosis

Lin Jikeng, Wu Congmin, Wang Dongtao
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引用次数: 1

Abstract

Adaptive Immune Algorithm based data mining (AIA-Data Mining) is presented for fault diagnosis of power transformer. The information entropy is used for the production of the initial population, which leads to convergence speed of the algorithm to be faster than that of the initial population produced by random. On the basis of that, the bi-level search Mechanism of the AIA further speeds up extraction of the decision-making table for the transformer fault diagnosis from the samples. Results from examples show that the method proposed is effective and feasible.
基于自适应免疫算法的数据挖掘在电力变压器故障诊断中的应用
提出了一种基于自适应免疫算法的数据挖掘方法,用于电力变压器故障诊断。利用信息熵产生初始种群,使得算法的收敛速度比随机产生初始种群的收敛速度快。在此基础上,AIA的双层搜索机制进一步加快了从样本中提取变压器故障诊断决策表的速度。算例结果表明,该方法是有效可行的。
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