Picture Fuzzy Knowledge Measure with Application to MADM

Devender Kumar Sharma, Koushal Singh, Surender Singh
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Abstract

The complementary dual of entropy is termed “knowledge measure” in recent studies concerning fuzzy and intuitionistic fuzzy sets. A picture fuzzy set is an extended and generalized form of fuzzy and intuitionistic fuzzy sets. The broader perspective of the picture fuzzy set inculcated the possibility of the formulation of a picture fuzzy knowledge measure and its potential implications. In this paper, we set up an axiomatic framework for obtaining a complementary dual of the picture fuzzy entropy. Subsequently, we derive two new knowledge measures that strictly follow the axiomatic requirements. Some empirical investigations establish the advantages of our proposed knowledge measure over the existing measures. We also present a novel multiple attribute decision-making (MADM) algorithm, wherein the proposed knowledge measure computes attribute weights and exhibits encouraging performance. The comparative analysis shows the potential implications and advantages of the proposed measures.
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图片模糊知识测度及其在MADM中的应用
在最近关于模糊集和直觉模糊集的研究中,熵的互补对偶被称为“知识测度”。图片模糊集是模糊和直觉模糊集的一种扩展和广义形式。图片模糊集的更广泛的视角灌输了制定图片模糊知识测度的可能性及其潜在含义。在本文中,我们建立了一个公理化的框架来获得图像模糊熵的互补对偶。随后,我们推导出两个严格遵循公理要求的新知识测度。一些实证调查证实了我们提出的知识测度相对于现有测度的优势。我们还提出了一种新的多属性决策(MADM)算法,其中所提出的知识测度计算属性权重并表现出令人鼓舞的性能。比较分析显示了拟议措施的潜在影响和优势。
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来源期刊
CiteScore
3.80
自引率
6.20%
发文量
57
审稿时长
20 weeks
期刊介绍: IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.
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