基于三次直觉模糊信息的多阶段决策分析的新相似度量和TOPSIS方法

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Intelligent & Fuzzy Systems Pub Date : 2023-10-25 DOI:10.3233/jifs-232085

Iqra Yaqoot, Muhammad Riaz, Ashraf Al-Quran, None Tehreem

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引用次数: 0

摘要

本研究利用三次直觉模糊集(CIFS)理论的创新概念，提出了一种新的多阶段决策分析方法。本文介绍了一种基于理想解相似性排序偏好(TOPSIS)的cif技术，作为MSDA问题的鲁棒方法，特别是用于癫痫疾病的诊断。为了实现这一目标，针对CIFS开发了新的相似性度量(SMs)，包括两个向量之间的余弦角、一种新的距离度量和余弦函数，它们被表示为三种不同类型的余弦相似性度量。所提出的CIF-TOPSIS方法被发现适合于精确的价值性能评级，并有望成为癫痫疾病诊断案例研究的可行方法。通过数值算例和对比分析，有效地验证了该方法的有效性和可靠性。

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New similarity measures and TOPSIS method for multi stage decision analysis with cubic intuitionistic fuzzy information

This research work proposes a novel approach for multi stage decision analysis (MSDA) using innovative concepts of cubic intuitionistic fuzzy set (CIFS) theory. The paper introduces CIF-technique for order preference by similarity to ideal solution (TOPSIS) as a robust method for MSDA problems, particularly for the diagnosis of epilepsy disorders. To achieve this goal, new similarity measures (SMs) are developed for CIFS, including the Cosine angle between two vectors, a new distance measure, and the Cosine function, presented as three different types of Cosine similarity measures. The proposed CIF-TOPSIS approach is found to be suitable for precise value performance ratings and is expected to be a viable approach for case studies in the diagnosis of epilepsy disorders. The efficiency and reliability of the proposed MSDA methods is efficiently carried through numerical examples and comparative analysis.

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来源期刊

Journal of Intelligent & Fuzzy Systems 工程技术-计算机：人工智能

CiteScore

3.40

自引率

10.00%

发文量

965

审稿时长

5.1 months

期刊介绍： The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.