Journal of Frontiers of Computer Science and Technology ›› 2018, Vol. 12 ›› Issue (5): 839-850.DOI: 10.3778/j.issn.1673-9418.1705019

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Multi-Cost Based Multi-Granulation Decision-Theoretic Rough Set Model

CHEN Jiajun1,2,3+, XU Huali1, WEI Yun4   

  1. 1. College of Electronics and Information Engineering, West Anhui University, Lu'an, Anhui 237012, China
    2. College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
    3. Key Laboratory of Embedded System and Service Computing (Tongji University), Ministry of Education, Shanghai 201804, China
    4. College of Railway Technology, Lanzhou Jiaotong University, Lanzhou 730000, China
  • Online:2018-05-01 Published:2018-05-07

多重代价多粒度决策粗糙集模型研究

陈家俊1,2,3+,徐华丽1,魏  赟4   

  1. 1. 皖西学院 电子与信息工程学院,安徽 六安 237012
    2. 同济大学 电子与信息工程学院,上海 201804
    3. 嵌入式系统与服务计算教育部重点实验室(同济大学),上海 201804
    4. 兰州交通大学 铁道技术学院,兰州 730000

Abstract: Decision-theoretic rough sets and multi-granulation rough sets are two important mechanisms of data processing. On the basis of decision-theoretic rough sets based on multi-cost and multi-granulation rough sets, by considering multi-cost matrix and multi-granularity thought, this paper introduces a weighted mean-cost strategy   into decision-theoretic rough set models, and proposes a multi-granulation decision-theoretic rough set model based on weighted multi-cost. In the incomplete information system, this paper discusses the pessimistic cost decision-theretic rough sets, optimistic cost decision-theoretic rough sets and weighted multi-cost multi-granulation decision-theoretic rough set models respectively, and describes the formulas of the whole decision costs for the above models. Finally, taking the pessimistic multi-granulation decision-theoretic rough set model based on weighted multi-cost for example, this paper analyzes the monotonicity of the decision positive region with respect to knowledge granularity sets, and proposes a definition of the granularity reduction based on the minimum decision cost. The model combines the decision-theoretic rough set model and multi-granulation rough set model with a more suitable method, which can solve the problems from multiple perspectives in the decision-theoretic rough set model.

Key words: decision-theoretic rough set, multi-granulation rough set, decision cost, reliability of cost

摘要: 决策粗糙集和多粒度粗糙集是两种重要的数据处理机制。在对多重代价决策粗糙集模型和多粒度粗糙集模型的研究基础上,通过综合考虑多重代价矩阵和多粒度思想,将权重均值代价策略引入决策粗糙集模型中,提出了一种基于权重多重代价的多粒度决策粗糙集模型。在不完备信息系统中,分析了悲观代价决策粗糙集、乐观代价决策粗糙集和权重多重代价多粒度决策粗糙集模型,并给出了以上各种模型的决策代价总代价计算公式。以权重多重代价悲观多粒度决策粗糙集模型为例,讨论了该模型下随着粒度的变化其正域的变化情况,并给出了一种基于代价最小化的粒度约简方法。该模型更好地结合了决策粗糙集模型和多粒度粗糙集模型,可从多角度分析解决决策粗糙集模型中的相关问题。

关键词: 决策粗糙集, 多粒度粗糙集, 决策代价, 代价认可度