摘要
目前,粗糙集理论大多数的研究应用都停留在静态表的基础上,但在实际中决策信息表的数据是在不停的增加更新当中,静态的方法在处理不停增加和变换的数据时有着很明显的局限性。在经典粗糙集理论的基础上,引入多粒度时间序列,对决策信息系统划分后,研究各个粒所产生的决策间的相互关联性,建立相关的粒度决策演化模型,并通过实例验证同源演化的有效可行性。
At present,most of the research applications of rough set theory remain in the field of static tables,but as the data in the real world is constantly increasing and updating, there are apparent limitation when dealing with the changing data. Multi-granularity time series is introduced in this paper based on the classical rough set theory.The relevance among decisions which are produced by each granule is studied and the relevant granular decision evolution model is built after the division of decision-making information system.Finally the feasibility of homologous evolution is formulated.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第20期117-120,共4页
Computer Engineering and Applications
基金
国家自然科学基金(No.60873104)
河南省高校新世纪优秀人才支持计划(No.2006HANCE T-19)
河南省教育厅自然科学基金(No.2008B520019)~~
关键词
多粒度
时间序列
决策演化
同源演化
multiple granularity
time series
decision evolution
homologous evolution
