基于多属性决策的 Diophantine 球形模糊集及其在微型技术机器人中的应用

IF 7.5 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Murugan Palanikumar , Nasreen Kausar , Željko Stević , Sarfaraz Hashemkhani Zolfani
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引用次数: 0

摘要

我们在多属性决策中引入了 Diophantine 球形模糊集方法的概念。球形模糊集是模糊集和区间值球形模糊集的新扩展。我们引入了三个新概念,如球面模糊加权平均算子、球面模糊加权几何算子、广义球面模糊加权平均算子和广义球面模糊加权几何算子。我们提供了一个数值示例来说明欧氏距离和汉明距离是如何相互作用的。Diophantine 球模糊数的应用包括代数运算中的幂等性、有界性、交换性和单调性。它们可以确定最优方案,而且更为人熟知和合理。我们的目标是通过比较专家意见和标准来确定最优选择。因此,模型的输出结果更加准确,并且在自然数范围内。加权平均距离和加权几何距离算子是基于聚合模型的距离度量。通过将讨论中的模型与文献中提出的模型进行比较,我们希望证明这些模型的价值和可靠性。这样可以更快、更简单、更实用地找到更好的解决方案。我们的目标是将专家评估与标准进行比较,确定哪种方案最合适。由于这些模型能得出更精确的解决方案,因此它们更准确,与使用 .NET技术的模型更相关。为了证明所提议的聚合操作的优越性和有效性,我们将其与现有方法进行了比较,并通过比较和敏感性分析得出结论,我们提议的技术更加有效和可靠。这项调查得出了一些耐人寻味的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diophantine spherical vague sets and their applications for micro-technology robots based on multiple-attribute decision-making
We introduce the concept of Diophantine spherical vague set approach to multiple-attribute decision-making. The Spherical vague set is a novel expansion of the vague set and interval valued spherical fuzzy set. Three new concepts have been introduce such as Diophantine spherical vague weighted averaging operator, Diophantine spherical vague weighted geometric operator, generalized Diophantine spherical vague weighted averaging operator and generalized Diophantine spherical vague weighted geometric operator. We provide a numerical example to show how Euclidean distance and Hamming distance interact. Applications of the Diophantine spherical vague number include idempotency, boundedness, commutativity and monotonicity in algebraic operations. They can determine the optimal option and are more well-known and reasonable. Our goal was to identify the optimal choice by comparing expert opinions with the criteria. As a result, the model’s output was more accurate as well as in the range of the natural number
. The weighted averaging distance and weighted geometric distance operators are distance measure that is based on aggregating model. By comparing the models under discussion with those suggested in the literature, we hoped to show their worth and reliability. It is possible to find a better solution more quickly, simply, and practically. Our objective was to compare the expert evaluations with the criteria and determine which option was the most suitable. Because they yield more precise solutions, these models are more accurate and more related to models with
. To show the superiority and the validity of the proposed aggregation operations, we compared it with the existing method and concluded from the comparison and sensitivity analysis that our proposed technique is more effective and reliable. This investigation yielded some intriguing results.
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来源期刊
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence 工程技术-工程:电子与电气
CiteScore
9.60
自引率
10.00%
发文量
505
审稿时长
68 days
期刊介绍: Artificial Intelligence (AI) is pivotal in driving the fourth industrial revolution, witnessing remarkable advancements across various machine learning methodologies. AI techniques have become indispensable tools for practicing engineers, enabling them to tackle previously insurmountable challenges. Engineering Applications of Artificial Intelligence serves as a global platform for the swift dissemination of research elucidating the practical application of AI methods across all engineering disciplines. Submitted papers are expected to present novel aspects of AI utilized in real-world engineering applications, validated using publicly available datasets to ensure the replicability of research outcomes. Join us in exploring the transformative potential of AI in engineering.
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