WANG Jiangrong;LUO Ziqin;WEN Hui;ZHAO Zhenxue;

• 1:Department of Technology Information Processing and Control Engineering
• 2:Lanzhou Petrochemical College of Vocational Technology
• 3:Department of Petrochemical Engineering
• 4:Lanzhou Petrochemical College of Vocational Technology

Abstract：

The common coal identification methods,which are influenced greatly by human factors,require high level sample data. While the accuracy is poor. Provided a grey correlation analysis method based on the information entropy. Combining the entropy theory and gray relational analysis,established the entropy coefficient grey correlation analysis of coal type identification model which applies to anthracite,bituminous coal and lignite. The accuracy of the model was tested by antidromic method. Taking the modeling coal sample and coal sample under test as research objects,compared the accuracy of entropy coefficient grey correlation degree analysis method and fuzzy identification method. The first analysis method has a high recognition efficiency to the two kinds of coal samples,both the efficiency are 100%. While the efficiency of the second method is 83. 33% and 75. 00%,the total accuracy rate is 81. 25%. The generalization and reliability of the entropy coefficient grey correlation analysis method is high.

Key Words： entropy coefficient;grey correlation analysis;coal sample recognition;fuzzy recognition method;model

Abstract:

Keywords:

Foundation: 甘肃省科技厅资助项目(1204GKCA004);; 甘肃省财政厅专项资金立项资助项目(甘财教[2013]116号)

Authors: WANG Jiangrong;LUO Ziqin;WEN Hui;ZHAO Zhenxue;

DOI: 10.13226/j.issn.1006-6772.2014.05.007

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