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A Short Survey on the Usage of Choquet Integral and its Associated Fuzzy Measure in Multiple Attribute Analysis

机译:Choquet积分及其相关模糊测度在多属性分析中的应用初探。

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Choquet integral operator is currently making inroads into many real multiple attribute analysis due to its ability on modeling the usual interactions held by the attributes during the aggregation process. Unfortunately, the process of identifying 2 n values of fuzzy measure prior to employing Choquet integral normally turns into a very complex one with the increasing number of attributes, n . On that note, this paper mainly reviews on some of the methods that have been proposed in reducing the complexity of identifying fuzzy measure values together with their pros and cons. The paper begins with a discussion on the aggregation process in multiple attribute analysis which then focuses on the usage of Choquet integral and its associated fuzzy measure before investigating some of the fuzzy measure identification methods. A simple numerical example to demonstrate the merit of using Choquet integral and the indications for future research are provided as well. The paper to some extent would be helpful in stimulating new ideas for developing simpler or enhanced versions of fuzzy measure identification methods.
机译:由于Choquet积分算子可以对聚合过程中属性所保持的通常交互进行建模,因此目前正涉足许多实际的多属性分析。不幸的是,在使用Choquet积分之前确定2 n个模糊测度值的过程通常会变成一个非常复杂的过程,其中属性n的数量不断增加。关于这一点,本文主要回顾了一些已提出的方法,这些方法可降低识别模糊度量值的复杂性及其优点和缺点。本文首先讨论了多属性分析中的聚合过程,然后在研究某些模糊度量识别方法之前,重点介绍了Choquet积分及其相关的模糊度量的用法。还提供了一个简单的数值示例来说明使用Choquet积分的优点,并提供了未来研究的指示。本文在某种程度上将有助于激发新思想,以开发更简单或增强版本的模糊度量识别方法。

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