Entropy-Based GLDS Method for Social Capital Selection of a PPP Project with q-Rung Orthopair Fuzzy Information

Liu, Li; Wu, Jihuai; Wei, Guiwu; Wei, Cun; Wang, Jie; Wei, Yu

doi:10.3390/e22040414

Cited by 36 publications

(22 citation statements)

References 69 publications

(78 reference statements)

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“…The comparison of the weight information in Example 1: (a) proposed combined weights, (b) combined weights by Peng and Huang, 40 (c) combined weights by Peng et al, 39 (d) objective weights by Liu et al, 20 (e) objective weights by Liu et al, 37 (f) objective weights by Rani and Mishra, 44 (g) objective weights by Garg, 14 and (h) objective weights by Gong et al 43 [Color figure can be viewed at wileyonlinelibrary.com]…”

Section: New Mcdm Methods For Mecs Selectionmentioning

confidence: 99%

“…From Figure 7E, compared with the original subjective weight information, the values of some objective weights have a three‐fold jump, such as

w_{4}

, which may change the final decision result process to some extent 37 . In addition, with the increase of

q

, there is an acceptable weight range fluctuation for other objective weights.…”

Section: New Mcdm Methods For Mecs Selectionmentioning

confidence: 99%

“…In the following, we give a comparison with some existing weight determining models, including objective weight determining models 20,37,43,44 and combined weight determining models. 33,39,40 1.…”

Section: The Sensitivity Analysis Of Weight Informationmentioning

confidence: 99%

“…The distance measure, correlation, and correlation coefficient with Minkowski type are successfully presented and proved in References [35,36]. Moreover, some entropy measures 37 are proposed for obtaining the weight information of diverse criteria with respect to alternatives. Peng and Liu 38 defined a systematic transformation framework of q‐ ROF information measure (entropy, SM, inclusion measure, and distance measure), gave detailed formulae of information measure, and finally successfully employed it in clustering analysis, medical diagnosis, and pattern recognition. …”

Section: Introductionmentioning

confidence: 99%

“…As a consequence, the first motivation is to deal these problems by proposing a new SM without the above three defects. Some existing weight determining models just consider objective weights 20,37,43,44 or subjective weights, which neglect the expert's subjective idea and ignore the internal statistical laws from the evaluation information. Moreover, some combined weight determining models have suffered from the DBZ problem 40 and antilogarithm by negative and zero issue 33 .…”

Section: Introductionmentioning

confidence: 99%

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q ‐Rung orthopair fuzzy decision‐making framework for integrating mobile edge caching scheme preferences

2021

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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.

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