An Algebraic Approach to Modular Inequalities Based on Interval-Valued Fuzzy Hypersoft Sets via Hypersoft Set-Inclusions

Rahman, Atiqe Ur; Saeed, Muhammad; Khan, Khuram Ali; Nosheen, Ammara; Mabela, Rostin Matendo

doi:10.1155/2022/1384541

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…Musa and Asaad 32 studied the bi-polarity of hs -set by developing a novel structure called bipolar hs -set and discussed its set-theoretic operations. Rahman et al 33–37 applied the concept of fhs -set in real world DM scenarios like medical diagnosis for heart diseases, set-theoretic and modular inequalities, supplier selection and risk analysis for real estate projects respectively. Ihsan et al 38,39 investigated various set-theoretic characteristics, set operations, and applications of hypersoft hybrids with an expert set environment to tackle with multi-decisive opinions of experts.…”

Section: Introductionmentioning

confidence: 99%

An innovative decisive framework for optimized agri-automobile evaluation and HRM pattern recognition via possibility fuzzy hypersoft setting

Rahman

Saeed

Garg

2022

Advances in Mechanical Engineering

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In multi-attribute decision-making system, decision-makers have to face two kinds of situations: (i) the opted parameters are likely to be classified into their respective parametric-valued sub-collections and (ii) the acceptance degree for approximate opinions of decision-makers is required to be assessed by possibility setting. The literature related to fuzzy soft sets is unable to provide any model which can tackle such situations collectively. Therefore, this study aims to address this scarcity through the development of a novel structure, that is, possibility fuzzy hypersoft set ([Formula: see text]-set). Firstly, the algebraic properties and set-theoretic operations of [Formula: see text]-set are characterized by mathematical illustration. Secondly, two algorithms based on AND and OR-operations of [Formula: see text]-set are proposed and authenticated through application in multi-attribute decision-making real-world problems for the evaluation of agri-automobile and then their suitability is judged through vivid comparison. Thirdly, similarity measures between [Formula: see text]-sets are formulated and validated with the help of application in recruitment-based pattern recognition and its significance is assessed through comparison with most relevant models. Lastly, the advantageous aspects of the proposed structure are analyzed by its comparison with possibility fuzzy soft set-like models by observing some important evaluating features.

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