JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2012, Vol. 42 ›› Issue (5): 91-95.

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The technique of gas disaster information feature extraction based on rough set theory

LI Hui1,2, HU Yun1,3, LI Cun-hua1   

  1. 1. Department of Computer Science, Huaihai Institute of Technology, Lianyungang 222005, China; 2. School of Information ＆ Electrical Engineering, China University of Mining ＆ Technology, Xuzhou 221008, China; 3. Department of Information Engineering, Nanjing University, Nanjing 110004, China
  • Received:2012-05-06 Online:2012-10-20 Published:2012-05-06

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Abstract: In order to accurately predict coal and gas outburst danger and to establish an effective earlywarming support system of gas in coal mine, a high efficient gas disaster feature extraction algorithm based on rough set was proposed in view of the characteristics of coal mine gas disaster. The algorithm first refined the gas disaster information matrix by using dimensionality reduction, then the entropy and max entropy in the concept of rough set theory were used to establish data mining model of gas disaster prediction. The effectiveness and practicality of rough set theory in the prediction of gas disaster and feature extraction was confirmed through practical application.

Key words: rough set theory, coal mine gas, feature extraction, information entropy

CLC Number: 

  • TP274
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