直觉模糊信息下基于熵测度的改进模糊TODIM方法

Sunitha Kumar, Satish Kumar
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摘要

直觉模糊集(IFS)是较现有模糊集结构适应更多不确定性的最广泛和重要的工具之一。本文提出了一种改进的权重信息部分已知的基于TODIM熵的多准则决策处理方法。首先,我们研究了ifs的基本概念和运行规律,以及ifs的精度和评分函数。提出了新的熵。其次,提出了基于中频信息的MCDM决策技术。最后给出了相关的数值算例,验证了所得结果的可靠性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved fuzzy TODIM method based on entropy measure under Intuitionistic Fuzzy Information
Intuitionistic fuzzy set (IFS) is one of the most extensive and important tool to accommodate more uncertainties than existing fuzzy set structures. In the present paper, we describe an improved entropy based on TODIM procedure for handling multi-criteria decision-making (MCDM) under IF setting and also the weight information is partially known. First, we study the basic notions and operating laws of IFSs, also the accuracy and score function of it. The new entropy has been proposed. Secondly, the IF information-based decision-making technique for MCDM is presented. Lastly, a numerical example is given related, to demonstrate that their results are credible and feasible.
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