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用于决策过程的复杂丢番图区间值毕达哥拉斯正规集

Complex Diophantine interval-valued Pythagorean normal set for decision-making processes.

作者信息

Palanikumar Murugan, Kausar Nasreen, Tharaniya Ponnaiah, Stević Željko, Tesgera Tolasa Fikadu

机构信息

Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 602105, India.

Department of Mathematics, Faculty of Arts and Science, Yildiz Technical University, Esenler, 34220, Turkey.

出版信息

Sci Rep. 2025 Jan 4;15(1):783. doi: 10.1038/s41598-024-82532-2.

Abstract

A novel method for solving the multiple-attribute decision-making problem is proposed using the complex Diophantine interval-valued Pythagorean normal set (CDIVPNS). This study aims to discuss aggregating operations and how they are interpreted. We discuss the concept of CDIVPN weighted averaging (CDIVPNWA), CDIVPN weighted geometric (CDIVPNWG), generalized CDIVPN weighted averaging (CGDIVPNWA) and generalized CGDIVPN weighted geometric (CGDIVPNWG). This study aimed to examine several aggregation operators using complex Diophantine interval-valued Pythagorean normal sets. We calculated the weighted average and geometric distance based on an aggregating model. We demonstrate that complex Diophantine interval-valued Pythagorean normal sets satisfy algebraic structures such as associative, distributive, idempotent, bounded, commutative and monotonic properties. In this study, we discuss the mathematical properties of the score and accuracy values. We provide an example of how enhanced score and accuracy values are used in the real world. Machine tool technology and computer science play essential roles in robots. To evaluate robotic systems, four factors must be considered such as tasks, precision, speed and completion of the work. Consequently, it is evident that the models are significantly influenced by the natural number ∇. To further demonstrate the effectiveness of the suggested approach, flowchart based multi-criteria decision-making is provided and applied to a numerical example. Additionally, a comparative study has been carried out to demonstrate the better results that the proposed approach provides when compared to current approaches.

摘要

提出了一种使用复丢番图区间值毕达哥拉斯模糊集(CDIVPNS)解决多属性决策问题的新方法。本研究旨在讨论聚合运算及其解释方式。我们讨论了CDIVPN加权平均(CDIVPNWA)、CDIVPN加权几何(CDIVPNWG)、广义CDIVPN加权平均(CGDIVPNWA)和广义CDIVPN加权几何(CGDIVPNWG)的概念。本研究旨在研究使用复丢番图区间值毕达哥拉斯模糊集的几种聚合算子。我们基于一个聚合模型计算了加权平均和几何距离。我们证明了复丢番图区间值毕达哥拉斯模糊集满足诸如结合性、分配性、幂等性、有界性、交换性和单调性等代数结构。在本研究中,我们讨论了得分和精度值的数学性质。我们给出了一个在现实世界中如何使用增强的得分和精度值的例子。机床技术和计算机科学在机器人中起着至关重要的作用。为了评估机器人系统,必须考虑四个因素,如任务、精度、速度和工作完成情况。因此,很明显这些模型受到自然数∇的显著影响。为了进一步证明所提方法的有效性,提供了基于流程图的多准则决策并应用于一个数值例子。此外,还进行了一项比较研究,以证明所提方法与当前方法相比能提供更好的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fa1/11700223/4539a5246d3f/41598_2024_82532_Fig1_HTML.jpg

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