An axiomatically supported divergence measures for q‐rung orthopair fuzzy sets

Khan, Muhammad Jabir; Alcantud, José Carlos R.; Kumam, Wiyada; Al-Kenani, Ahmad N.

doi:10.1002/int.22545

Cited by 21 publications

(17 citation statements)

References 31 publications

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“…Here, this study focuses on the approach of preprocessing the body of evidence by utilizing divergence measure to calculate the discrepancy or degree of conflict among evidence, as divergence measure is widely used in decision-making. 55,56 Definition 4 Bχ ( 2 divergence). Let m 1 and m 2 be two independent BPAs.…”

Section: Belief Divergence Measuresmentioning

confidence: 99%

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A novel belief χ2 ${\chi }^{2}$ divergence for multisource information fusion and its application in pattern classification

Zhang

Xiao

2022

Int J of Intelligent Sys

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Dempster-Shafer (D-S) evidence theory is invaluable in the domain of multisource information fusion for handing uncertainty problems. However, there may be counter-intuitive phenomenon when facing highly conflicting information. In this paper, a novel symmetric enhanced belief χ 2 divergence measure, called SEBχ 2 , is proposed to measure the discrepancy between basic probability assignments (BPAs). The SEBχ 2 divergence consider the features of BPAs as the influence of both single-element subsets and multielement subsets is taken into account. Furthermore, the SEBχ 2 divergence is proven to be symmetric, nonnegative and nondegenerate, which are desirable properties for conflict management. Then, a new algorithm for multisource information fusion based on the SEBχ 2 divergence measure is derived. Finally, an application for pattern classification is used to illustrate the superiority of the proposed SEBχ 2 divergence measure-based fusion method over other existing well-known and recent related works with a better classification accuracy of 94.39%.

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Section: Belief Divergence Measuresmentioning

confidence: 99%

“…Some scholars improved the fusion model, while others did data processing before fusion. Here, this study focuses on the approach of preprocessing the body of evidence by utilizing divergence measure to calculate the discrepancy or degree of conflict among evidence, as divergence measure is widely used in decision‐making 55,56 …”

Section: Preliminariesmentioning

confidence: 99%

A novel belief χ2 ${\chi }^{2}$ divergence for multisource information fusion and its application in pattern classification

Zhang

Xiao

2022

Int J of Intelligent Sys

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“…Entropy and discrimination measure, as the information measures, have been proven as important tools in the doctrine of Zadeh’s FS and its generalizations. Although, very few authors (Peng and Liu, 2019 ; Verma, 2020 ; Khan et al, 2021a ; Mishra and Rani, 2021 ) have concentrated their interest in the development of “q-rung orthopair fuzzy (q-ROF)” information measures. Also, no one has employed the concepts of entropy and discrimination measure to estimate the objective criteria weights for evaluation of SWDM selection problem.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the theory of q-ROFSs is proven as more flexible and superior way to model the vagueness and imprecision of complex MCDM problems. In the literature, very few authors (Peng and Liu, 2019 ; Verma, 2020 ; Chakraborty and Kumar, 2021 ; Khan et al 2021a ; Mishra and Rani, 2021 ) have concentrated their interest in the development of q-rung orthopair fuzzy entropy and discrimination measure, but these measures have some counter intuitive cases. In the literature (Darko and Liang, 2020 ; Garg and Chen, 2020 ; Khan et al, 2021a , b ; Arsu and Ayçin, 2021 ; Kumar and Chen, 2022 ; Deveci et al, 2022a ), the weight of each DE was directly assigned by the authors, which can cause subjective uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Entropy and discrimination measures based q-rung orthopair fuzzy MULTIMOORA framework for selecting solid waste disposal method

Mishra¹,

Rani

Pamučar

et al. 2022

Environ Sci Pollut Res

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Fastest growing population, rapid urbanization, and growth in the disciplines of science and technology cause continually development in the amount and diversity of solid waste. In modern world, evaluation of an appropriate solid waste disposal method (SWDM) can be referred as multi-criteria decision-making (MCDM) problem due to involvement of several conflicting quantitative and qualitative sustainability indicators. The imprecision and ambiguity are usually arisen in SWDM assessment problem, and the q-rung orthopair fuzzy set (q-ROFS) has been recognized as one of the adaptable and valuable ways to tackle the complex uncertain information arisen in realistic problems. In the context of q-ROFSs, entropy is a significant measure for depicting fuzziness and uncertain information of q-ROFS and the discrimination measure is generally used to quantify the distance between two q-ROFSs by evaluating the amount of their discrimination. Thus, the aim of this study is to propose a novel integrated framework based on multi-attribute multi-objective optimization with the ratio analysis (MULTIMOORA) method with q-rung orthopair fuzzy information (q-ROFI). In this approach, an integrated weighting process is presented by combining objective and subjective weights of criteria with q-ROFI. Inspired by the q-rung orthopair fuzzy entropy and discrimination measure, objective weights of criteria are estimated by entropy and discrimination measure-based model. Whereas, the subjective weights are derived based on aggregation operator and the score function under q-ROFS environment. In this respect, novel entropy and discrimination measure are proposed for q-ROFSs. Furthermore, to display the feasibility and usefulness of the introduced approach, a case study related to SWD method selection is presented under q-ROFS perspective. Finally, comparison and sensitivity investigation are presented to confirm the robustness and solidity of the introduced approach.

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“…The authors of Ref. 19 critically analyzed the existing attempts of q-rung orthopair fuzzy divergence measure and formulated an improved divergence measure. Based on the proposed measure, they extended multi-attribute border approximation area comparison decision method for selection problems.…”

Section: Introductionmentioning

confidence: 99%

Cosine similarity measures between q-rung orthopair linguistic sets and their application to group decision making problems

Ali

Naeem

2022

Sci Rep

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The q-rung orthopair linguistic set (q-ROLS), a combined version of linguistic term sets and q-rung orthopair fuzzy set, is an efficient mathematical tool to accomplish the imprecise information while solving the decision-making problems. Under this environment, we propose additional operations and relations to deal with the decision information, and some properties are well proved. Furthermore, we propound some cosine similarity measures and weighted cosine similarity measures for q-ROLSs based on the traditional cosine similarity measures with a brief study of related properties. In the proposed similarity measures, various linguistic scale functions are utilized in order to take into account the semantics of linguistic terms. Besides this, we employ the stated q-rung orthopair linguistic similarity measures to multi-criteria group decision making problems, in which the weights of DMs are delineated by the projection of individual decisions on the ideal decision results. At last, a numerical example is used to demonstrate the practicality of the suggested technique, and its efficacy is validated by comparison with prevailing techniques. The suggested method’s sensitivity and stability analyses are also provided.

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An axiomatically supported divergence measures for q‐rung orthopair fuzzy sets

Cited by 21 publications

References 31 publications

A novel belief χ2 ${\chi }^{2}$ divergence for multisource information fusion and its application in pattern classification

A novel belief χ2 ${\chi }^{2}$ divergence for multisource information fusion and its application in pattern classification

Entropy and discrimination measures based q-rung orthopair fuzzy MULTIMOORA framework for selecting solid waste disposal method

Cosine similarity measures between q-rung orthopair linguistic sets and their application to group decision making problems

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