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Interval‐valued Pythagorean fuzzy extended Bonferroni mean for dealing with heterogenous relationship among attributes
Author(s) -
Liang Decui,
Darko Adjei Peter,
Xu Zeshui
Publication year - 2018
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21973
Subject(s) - pythagorean theorem , interval (graph theory) , bonferroni correction , mathematics , fuzzy set , fuzzy logic , partition (number theory) , operator (biology) , computer science , artificial intelligence , data mining , statistics , combinatorics , geometry , biochemistry , chemistry , repressor , transcription factor , gene
Owing to the information insufficiency, it might be difficult for decision makers to precisely evaluate their assessments in real decision‐making. As a new extension of the Pythagorean fuzzy sets, the interval‐valued Pythagorean fuzzy sets (IVPFSs) can availably provide enough input space for decision makers to evaluate their assessments with interval numbers. By extending the Bonferroni mean to model the heterogeneous interrelationship among attributes, the extended Bonferroni mean (EBM) was examined. Considering the partition structure of relationship among the attributes, we introduce the EBM into the interval‐valued Pythagorean fuzzy environment and develop two new aggregation operators, namely, interval‐valued Pythagorean fuzzy extended Bonferroni mean and weighted interval‐valued Pythagorean fuzzy extended Bonferroni mean (WIVPFEBM) operators. Meanwhile, some of their special cases and properties are also deeply discussed. Subsequently, by employing the WIVPFEBM operator, we propose an approach for multiple attribute decision making with IVPFSs. Finally, a practical illustration of the E‐commerce project selection problem is investigated by our proposed method, which successfully demonstrates the applicability of our results.