Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211200142-6.doi: 10.11896/jsjkx.211200142

• Big Data & Data Science • Previous Articles     Next Articles

Attribute Reduction Algorithm Based on a New q-rung orthopair Fuzzy Cross Entropy

WANG Zhi-qiang, ZHENG Ting-ting, SUN Xin, LI Qing   

  1. School of Mathematical Science,Anhui University,Hefei 230601,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:WANG Zhi-qiang,born in 1997,postgraduate.His main research interests include granular computing and so on.
    ZHENG Ting-ting,born in 1978,Ph.D,professor.Her main research interests include granular computing and know-ledge discovery.
  • Supported by:
    National Natural Science Foundation of China(61806001).

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Abstract: Entropy is an important means to describe the degree of uncertainty of fuzzy sets.In order to reflect the ambiguity produced by the comparison between the membership degree and the non-membership degree in the q-rung orthopair fuzzy set,a related score function is first proposed.Taking into account the shortcomings of the similarity measures of most of the current q-rung orthopair fuzzy sets,a q-rung orthopair fuzzy set cross entropy is proposed,which is more in line with people’s intuition.As there is relatively little research on attribute reduction of q-rung orthopair fuzzy information system at present,through property discussion and theoretical proof,it is found that this kind of cross entropy can be better applied to attribute reduction of q-rung orthopair fuzzy information system.The related attribute reduction algorithm is presented,and an example is given to illustrate the rationality of this algorithm.Secondly,a method to convert ordinary information system into q-rung orthopair fuzzy information system is given.Finally,the rationality and effectiveness of this method are verified by calculating multiple databases in UCI,which provides new ideas for q-rung orthopair fuzzy information system data preprocessing.

Key words: q-rung orthopair fuzzy set, J-divergence, Information system, Cross entropy, Attributes reduction

CLC Number: 

  • TP18
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