Integrated personalized decision method with q-rung orthopair fuzzy data for underground natural gas storage site decisions

IF 7.2 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Applied Soft Computing Pub Date : 2025-05-30 DOI:10.1016/j.asoc.2025.113384

Raghunathan Krishankumar , Fatih Ecer , Pratibha Rani , Dragan Pamucar , Serhat Yüksel , Hasan Dinçer

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引用次数: 0

Abstract

Location selection for underground natural gas storage is a multifaceted decision-making problem, as diverse factors are involved. Earlier studies on location selection for natural gas faced challenges such as uncertainty handling, methodical estimation of experts' reliability, capturing hesitation during factor significance calculation, and personalized location ordering. Therefore, the present work develops a novel integrated weighted aggregated sum product assessment (WASPAS) methodology with generalized (q-rung orthopair) fuzzy information, considering three dimensions of uncertainty: membership grade, hesitancy grade, and non-membership grade, with a flexible window allowing experts easy preference articulation. The reliability of experts is calculated using the Cronbach measure, and the importance of the criteria is computed based on the regret factor. A ranking algorithm is developed with a modified weighted aggregated sum product assessment formulation and choice vector to obtain personalized ordering of natural gas locations. The usefulness is illustrated using a case study of location selection for underground natural gas storage in India. Results show that, political acceptance is the most crucial indicator when selecting an optimal underground storage location for natural gas. The outcomes concluded that the introduced integrated framework (i) is robust, even after alterations are realized for the weights of the criteria and strategy values, (ii) produces rank orders that are consistent with the earlier models, and (iii) yields broader rank values, to support better discrimination of alternative locations and appropriate backup management compared to the extant model. Finally, the benefits, shortcomings, and implications are discussed. The model introduced can be a novel guide for natural gas location selection and can aid investors in planning their investments.

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基于q阶正交模糊数据的地下天然气库选址综合个性化决策方法

地下天然气储库选址是一个涉及多种因素的多面决策问题。早期的天然气选址研究面临着诸多挑战，如不确定性处理、专家可靠性的系统估计、因素显著性计算过程中的犹豫、个性化选址排序等。因此，本工作开发了一种新的综合加权汇总和产品评估（WASPAS）方法，该方法具有广义（q-rung orthopair）模糊信息，考虑不确定性的三个维度：成员等级，犹豫等级和非成员等级，具有灵活的窗口，使专家易于偏好表达。专家的信度是用Cronbach测量来计算的，标准的重要性是根据后悔因子来计算的。采用改进的加权总和积评价公式和选择向量，提出了一种天然气位置个性化排序算法。以印度地下天然气储库选址为例，说明了该方法的实用性。结果表明，政治接受度是天然气地下储气库最优选址的关键指标。结果表明，引入的综合框架(i)是稳健的，即使在改变了标准和策略值的权重之后，（ii）产生与早期模型一致的排名顺序，（iii）产生更广泛的排名值，以支持与现有模型相比更好地区分备选地点和适当的备份管理。最后，讨论了其优点、缺点和影响。该模型为天然气选址提供了一种新的指导，可以帮助投资者进行投资规划。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Soft Computing 工程技术-计算机：跨学科应用

CiteScore

15.80

自引率

6.90%

发文量

874

审稿时长

10.9 months

期刊介绍： Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities. Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.