消费类电子智能交通系统的创新评估框架:利用$q$阶图像模糊超软Schweizer-Sklar聚合算子

Badiea Abdulkarem Mohammed;Himanshu Dhumras;Varun Shukla;Rakesh Kumar Bajaj;Zeyad Ghaleb Al-Mekhlafi
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引用次数: 0

摘要

以消费电子产品为支撑的智能交通系统(ITS)的发展对现代城市交通具有重要意义。然而,为了评价这些系统,必须处理复杂的、不确定的和相互关联的因素,如技术可行性、经济可行性和风险评估。传统的多准则决策方法不能很好地管理这些不确定性。本文提出了一种基于新的Schweizer-Sklar (SS)聚合运算和q阶图像模糊超软集($q$-RPFHSS)的评价框架来解决这一问题。这些算子通过对子参数化不确定性进行建模来提高决策精度。将该方法应用于5个城市的ITS部署排名,与现有方法相比,显示出出色的灵活性和精度。对比分析说明了所提出的方法在ITS战略决策中的鲁棒性,确保了更可靠和适应性的评估过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Innovative Evaluation Framework for Consumer Electronics-Enabled Intelligent Transportation Systems: Leveraging $q$-Rung Picture Fuzzy Hypersoft Schweizer-Sklar Aggregation Operators
The development of intelligent transportation systems (ITS), supported by consumer electronics, is important for modern urban mobility. However, to evaluate these systems, complex, uncertain and interrelated factors, such as technological feasibility, economic viability, and risk assessment, must be addressed. Traditional multi-criteria decision-making (MCDM) approaches do not manage these uncertainties well. This article presents a novel assessment framework based on new Schweizer-Sklar (SS) aggregation operations and the q-rung picture fuzzy hypersoft set ($q$-RPFHSS) to tackle this problem. These operators enhance decision-making accuracy by modeling sub-parameterized uncertainties. The proposed method is applied to rank five cities for the deployment of ITS, showing excellent flexibility and precision compared to existing methods. Comparative analyses illustrate the robustness of the proposed approach in strategic decision-making for ITS, ensuring a more reliable and adaptive evaluation process.
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CiteScore
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