Evidence based decision analysis and support

Jianbo Yang, Dongling Xu
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Abstract

The evidential reasoning (ER) approach was developed to support multiple criteria decision analysis (MCDA). It is based on the Dampster's combination rule for criteria aggregation and belief function for treating ignorance. In the original ER approach, however, alternative ranking depends on the accurate estimation of a value function, which may be difficult in certain decision environments. In this paper, the link and difference between the ER algorithm and Dampster's combination rule are analysed first. A new alternative ranking method is then investigated as an integrated part of the enhanced ER approach.
基于证据的决策分析和支持
证据推理(ER)方法的发展是为了支持多准则决策分析(MCDA)。它基于Dampster的标准聚合组合规则和治疗无知的信念函数。然而,在最初的ER方法中,备选排序依赖于对价值函数的准确估计,这在某些决策环境中可能很困难。本文首先分析了ER算法与Dampster组合规则的联系和区别。然后研究了一种新的替代排序方法,作为增强型ER方法的一个组成部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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