基于圆形毕达哥拉斯模糊软爱因斯坦聚合算子的公交服务质量评价

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Zeeshan Ali, Muhammad Waqas, Sarbast Moslem, Tapan Senapati, Domokos Esztergár-Kiss
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引用次数: 0

摘要

本文介绍了圆毕达哥拉斯模糊软集(CPFS)技术及其可靠性质,如代数可选定律和爱因斯坦运算定律。我们进一步发展了CPFS爱因斯坦加权平均算子(CPFSEWA)和CPFS爱因斯坦加权几何算子(CPFSEWG),突出了它们的基本性质。此外,我们将基于平均解距离(EDAS)方法的评价与CPFSEWA和CPFSEWG算子相结合,并通过相关实例进行了说明。将所提出的技术应用于多属性决策(MADM)方法,改进了公共汽车运输服务质量的评价过程。具体来说,对都柏林16路公交车路线进行了分析,重点是可靠性、速度、可接近性、直接性和时间可用性等标准。我们的方法评估了各种替代方案,包括购买新巴士、搬迁巴士站、改变时间表、引入新巴士线路以及改善司机培训。最后,我们将提出的排序值与现有技术的排序值进行了比较,证明了基于cpfs的方法的灵活性和熟练性。这项综合评估旨在为政策制定者和运营商提供改善公共交通服务的有力工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of public bus transport service quality based on circular Pythagorean fuzzy soft Einstein aggregation operators

In this article, we introduce the technique of circular Pythagorean fuzzy soft (CPFS) sets and their reliable properties, such as algebraic optional laws and Einstein operational laws. We further develop the CPFS Einstein weighted averaging (CPFSEWA) operator and the CPFS Einstein weighted geometric (CPFSEWG) operator, highlighting their fundamental properties. Additionally, we integrate the evaluation based on the distance from average solution (EDAS) method with the CPFSEWA and CPFSEWG operators, illustrated through relevant examples. The multi-attribute decision-making (MADM) method is applied using the proposed techniques, enhancing the evaluation process of public bus transport service quality. Specifically, the Dublin Bus 16 route is analyzed, focusing on criteria such as reliability, speed, approachability, directness, and time availability. Our methodology evaluates various alternatives, including the purchase of new buses, relocation of bus stops, changes in timetables, introduction of new bus lines, and improvement in driver training. Finally, we compare the proposed ranking values with those from existing techniques, demonstrating the flexibility and proficiency of the CPFS-based approach. This comprehensive evaluation aims to provide policymakers and operators with robust tools for improving public transport services.

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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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