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

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Journal of Vibration and Shock ›› 2009, Vol. 28 ›› Issue (2) : 82-85,1.

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

Wu Xing1,Chi Yilin1,Chen Jin2

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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.

Key words

feature mining / entropy measurement / genetic algorithm / rough set

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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