基于覆盖的多重代价粗糙决策分析方法

doi:10.11896/j.issn.1002-137X.2019.05.032

摘要/Abstract

摘要： 为弥补传统决策粗糙模型要求概念间无交叉且忽略了多重代价矩阵的重要性的不足,文中提出了基于覆盖的加权多重代价决策粗糙集模型。首先,分析了基于等价关系的多重代价决策粗糙模型中存在粒度分类过细的问题,综合考虑了代价矩阵的数量关系和相对重要程度,引入了覆盖和代价矩阵权重对其进行改进,定义了新模型的上、下近似;然后,针对4种基于覆盖的多重代价决策粗糙集,讨论了其相互关系,并对相关性质和定理进行证明;最后,通过医疗诊断的实例验证了模型的有效性和实用性。

关键词: 多重代价矩阵, 覆盖, 决策粗糙集, 权重

Abstract: In order to make up for the deficiency of decision-theoretic rough model that there is no crossover between concepts and ignores the importance of multi-cost matrices,a rough set of multi-cost decision-theoretic rough set based on covering approximate space was proposed.Firstly,the problem of excessive granularity classification in the decision-theoretic rough set based on the equivalence relation was analyzed.Considering the quantitative relation and the importance among the cost matrices,covering and weighted multiple cost matrices were introduced to improve the covering multi-cost decision-theoretic rough set.Then,for four kinds of rough set of multi-cost decision-theoretic rough set based on covering approximate space,the rough approximations of knowledge were acquired and the relationship with each other was discussed.And relevant theorems and properties were proved. Finally,the feasibility and effectiveness of the method was verified by the case of medical diagnosis.

Key words: Covering, Decision-theoretic rough set, Multiple cost matrices, Weight

中图分类号:

TP181

骆公志, 许鑫鑫. 基于覆盖的多重代价粗糙决策分析方法[J]. 计算机科学, 2019, 46(5): 209-213. https://doi.org/10.11896/j.issn.1002-137X.2019.05.032

LUO Gong-zhi, XU Xin-xin. Multi-cost Decision-theoretic Rough Set Based on Covering Approximate Space[J]. Computer Science, 2019, 46(5): 209-213. https://doi.org/10.11896/j.issn.1002-137X.2019.05.032

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