Computer Science ›› 2021, Vol. 48 ›› Issue (10): 98-106.doi: 10.11896/jsjkx.200800074

• Artificial Intelligence • Previous Articles     Next Articles

Optimal Granulation Selection Method Based on Multi-granulation Rough Intuitionistic Hesitant Fuzzy Sets

XUE Zhan-ao, SUN Bing-xin, HOU Hao-dong, JING Meng-meng   

  1. College of Computer and Information Engineering,Henan Normal University,Xinxiang,Henan 453007,China
    Engineering Lab of Henan Province for Intelligence Business & Internet of Things,Xinxiang,Henan 453007,China
  • Received:2020-08-12 Revised:2020-10-22 Online:2021-10-15 Published:2021-10-18
  • About author:XUE Zhan-ao,born in 1963,Ph.D,professor,is a senior member of China Artificial Intelligence.His main research interests include basic theory of artificial intelligence,rough sets theory,fuzzysets,and three-way decision theory.
  • Supported by:
    National Natural Science Foundation of China(62076089,61772176) and Scientific and Technological Project of Henan Province of China(182102210078,182102210362).

Abstract: In order to obtain the optimal granulations after reduction from the intuitionistic hesitant fuzzy decision information system with multiple attributes,this paper deals with the uncertain information in this system from the perspective of multi-gra-nulation rough sets,and studies optimal granulation selection method based on multi-granulation rough intuitionistic hesitant fuzzy sets.Firstly,on the basis of intuitionistic hesitant fuzzy sets,attribute information is introduced,and the concept of rough intui-tionistic hesitant fuzzy sets is given.Then four upper and lower approximation models of optimistic and pessimistic multi-granulation rough intuitionistic hesitant fuzzy sets are proposed,and the related properties are discussed.Secondly,mainly based on the lower approximation of the pessimistic multi-granulation rough intuitionistic hesitant fuzzy set,this paper defines the granu-lation quality similarity degree and internal/external granulation importance degree,and the related algorithm of optimal granulation selection is designed.Finally,through the wine evaluation case,optimal granularities are calculated based on the four cases of optimistic and pessimistic multi-granulation rough intuitionistic hesitant fuzzy set's upper and lower approximation,then analyzes results.It is verified that algorithms are effective for the reduction of intuitionistic hesitant fuzzy decision information system.

Key words: Granulation importance degree, Intuitionistic hesitant fuzzy sets, Multi-granulation, Optimal granulation selection, Rough sets

CLC Number: 

  • TP181
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