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Rough approximation of a preference relation by a multi-attribute dominance for deterministic, stochastic and fuzzy decision problems

机译:确定性,随机性和模糊决策问题的多属性优势对偏好关系的粗略近似

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摘要

The case of mixed data in which attributes have a different nature is not well known in current literature, although it is essential from a practical point of view. This situation is particularly frequent in risk management modelling which incorporates various degrees of precision of the variables measured, and can also be noted in a planning context for project evaluation problems taking into account information of a mixed (qualitative and quantitative) type. For a set of alternatives evaluated by a set of attributes, three kinds of evaluations are considered in this paper: deterministic, stochastic, or fuzzy with relation to each attribute. The mixed-data multi-attribute dominance for a reduced number of attributes (MMD_R) is proposed to model the preferences in this kind of problem. The approach is based on the dominance-based rough set approach proposed by Greco, Matarazzo and Slowinski.
机译:尽管从实践的角度来看这是必不可少的,但是在混合数据中属性具有不同性质的情况在当前文献中并不为人所知。这种情况在风险管理模型中特别常见,该模型结合了所测变量的各种精确度,并且在规划环境中还可以在考虑混合(定性和定量)类型信息的情况下注意到项目评估问题。对于由一组属性评估的一组替代方案,本文考虑了三种评估:与每个属性相关的确定性,随机性或模糊性。提出了针对属性数量减少的混合数据多属性优势(MMD_R),以对此类问题中的偏好进行建模。该方法基于Greco,Matarazzo和Slowinski提出的基于优势的粗糙集方法。

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