Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6): 131-141.doi: 10.11896/jsjkx.220800149

• Granular Computing & Knowledge Discovery • Previous Articles     Next Articles

Optimal Scale Selection and Rule Acquisition in Inconsistent Generalized Decision Multi-scale Ordered Information Systems

YANG Ye1, WU Weizhi1,2, ZHANG Jiaru1   

  1. 1 School of Information Engineering,Zhejiang Ocean University,Zhoushan,Zhejiang 316022,China
    2 Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province(Zhejiang Ocean University),Zhoushan,Zhejiang 316022,China
  • Received:2022-08-15 Revised:2022-11-28 Online:2023-06-15 Published:2023-06-06
  • About author:YANG Ye,born in 1999,postgraduate.Her main research interests include rough set and granular computing.WU Weizhi,born in 1964,Ph.D,professor.His main research interests include rough set,granular computing,data mining and artificial intelligence.
  • Supported by:
    National Natural Science Foundation of China(61976194,62076221).

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Abstract: Granular computing imitates human being's thinking.It shows great promise as a new way for data mining and know-ledge discovery in the context of big data.To solve the problem of knowledge acquisition in inconsistent generalized decision multi-scale ordered information systems,by employing evidence theory,the optimal scale combination and rule extraction in inconsistent generalized decision multi-scale ordered information systems are studied.Dominance relations are first introduced into decision multi-scale information systems,and some basic concepts in decision multi-scale ordered information systems are introduced.With reference to the notion of scale combinations in inconsistent generalized decision multi-scale ordered information systems,representations of information granules as well as lower and upper approximations of sets under different scale combinations are presented and their relationships are examined.With different scales of decisions,several types of optimal scale combinations in inconsistent generalized decision multi-scale ordered information systems are further defined and their relationships are clarified.Finally,a method of discernibility matrix attribute reduction and rule acquisition based on generalized dominance decision functions are explored.

Key words: Evidence theory, Multi-scale ordered information systems, Scale selection, Rough sets, Granular computing

CLC Number: 

  • TP182
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