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q ‐Rung orthopair fuzzy decision‐making framework for integrating mobile edge caching scheme preferences
Author(s) -
Peng Xindong,
Huang Haihui,
Luo Zhigang
Publication year - 2021
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.22377
Subject(s) - computer science , multiple criteria decision analysis , fuzzy logic , entropy (arrow of time) , measure (data warehouse) , mathematical optimization , data mining , fuzzy set , algorithm , mathematics , artificial intelligence , physics , quantum mechanics
Mobile edge caching scheme (MECS) can determine where, how, and what to cache on user equipment by employing its own storage. When considering the performance of MECS, it is often full of uncertainty. The q‐ rung orthopair fuzzy set ( q‐ ROFS), characterized by membership and nonmembership degrees with adjustable parameter q , is quite a high‐efficiency way to capture uncertainty. In this paper, first, information measure (entropy, distance measure, and similarity measure)‐based area difference under the q‐ rung orthopair fuzzy ( q‐ ROF) circumstance is studied along with their detailed proofs. Then, we present a comprehensive weight‐determination method by combining objective weights (determining by entropy) and subjective weights (given by experts) as combined weights, which can effectually alleviate the unconscionable influence of extreme data on evaluation results and simultaneously reflect objective data and subjective emotion. Moreover, q‐ ROF score function‐based distance measure is presented for dealing with a value comparison problem. Later, q‐ ROF multicriteria decision‐making (MCDM) method called total area based on orthogonal vector (TAOV) is introduced. Moreover, its feasibility is illustrated by MECS selection problem. Finally, a comparison of some existing MCDM methods and the proposed method is constructed for displaying their effectiveness. This proposed method can effectively avoid counterintuitive phenomena, eliminate antilogarithm by negative and zero issue, and has no division by zero issue.