基于熵度量和遗传算法的粗糙集归约方法

伍 星;迟毅林;陈 进

振动与冲击 ›› 2009, Vol. 28 ›› Issue (2) : 82-85,1.

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PDF(1274 KB)
振动与冲击 ›› 2009, Vol. 28 ›› Issue (2) : 82-85,1.
论文

基于熵度量和遗传算法的粗糙集归约方法

  • 伍 星1,迟毅林1,陈 进2
作者信息 +

A FEATURE REDUCTION METHOD OF ROUGH SET BASED ONENTROPY MEASUREMENT AND GENETIC ALGORITHM

  • Wu Xing1,Chi Yilin1,Chen Jin2
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摘要

在研究数据挖掘技术的基础上,建立了旋转机械故障诊断的特征挖掘模型。针对传统粗糙集归约存在的最佳约简不唯一和约简计算时间长的问题,提出了一种以熵重要度为指标的最佳特征评价方法和一种基于遗传算法的粗糙集特征归约算法。最后,设计并实现了一个专用特征挖掘工具RMFMiner,通过转子故障模拟数据集和UCI机器学习数据库验证了该算法的有效性。

Abstract

A feature mining model is set up for rotating machine fault diagnosis, based on data mining. There are two problems in tranditional reduction of rough set. One is uniqueness of the best reduction; another is to spend much time for calculating redcution. This paper proposes a feature reduction algorithm of rough set (RS) based on entropy importance and genetic algorithm (GA). In the end of this paper, a feature mining tool, RMFMiner, is designed and implemented. This algorithm is employed to reduce the faults of rotating machinery and UCI data set. It is proved to be effective.

关键词

特征挖掘 / 熵度量 / 遗传算法 / 粗糙集

Key words

feature mining / entropy measurement / genetic algorithm / rough set

引用本文

导出引用
伍 星;迟毅林;陈 进. 基于熵度量和遗传算法的粗糙集归约方法 [J]. 振动与冲击, 2009, 28(2): 82-85,1
Wu Xing;Chi Yilin;Chen Jin. A FEATURE REDUCTION METHOD OF ROUGH SET BASED ONENTROPY MEASUREMENT AND GENETIC ALGORITHM[J]. Journal of Vibration and Shock, 2009, 28(2): 82-85,1
中图分类号: TP391   

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