不协调广义决策多尺度序信息系统的最优尺度选择与规则提取  

Optimal Scale Selection and Rule Acquisition in Inconsistent Generalized Decision Multi-scale Ordered Information Systems

作　　者：杨烨 吴伟志 张嘉茹 YANG Ye;WU Weizhi;ZHANG Jiaru(School of Information Engineering,Zhejiang Ocean University,Zhoushan,Zhejiang 316022,China;Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province(Zhejiang Ocean University),Zhoushan,Zhejiang 316022,China)

机构地区：[1]浙江海洋大学信息工程学院,浙江舟山316022 [2]浙江省海洋大数据挖掘与应用重点实验室(浙江海洋大学),浙江舟山316022

出　　处：《计算机科学》2023年第6期131-141,共11页Computer Science

基　　金：国家自然科学基金(61976194,62076221)。

摘　　要：粒计算模拟人类思考问题的模式,在大数据挖掘和知识发现方面有独特优势。针对不协调的广义决策多尺度序信息系统的知识获取问题,利用证据理论来研究不协调的广义决策多尺度序信息系统的最优尺度选择与规则提取。首先,将优势关系引入决策多尺度信息系统中,并介绍广义决策多尺度序信息系统的相关概念;其次,通过引入不协调广义决策多尺度序信息系统的尺度组合概念,给出不同尺度组合下信息粒和集合的下近似与上近似的表示及其相互关系,并进一步定义了几种针对不同决策的不协调广义决策多尺度序信息系统的最优尺度组合概念,讨论了它们之间的关系;最后,给出了基于广义优势决策函数的辨识矩阵属性约简与规则提取方法。Granular computing imitates human being's thinking.It shows great promise as a new way for data mining and know-ledge discovery in the context of big data.To solve the problem of knowledge acquisition in inconsistent generalized decision multi-scale ordered information systems,by employing evidence theory,the optimal scale combination and rule extraction in inconsistent generalized decision multi-scale ordered information systems are studied.Dominance relations are first introduced into decision multi-scale information systems,and some basic concepts in decision multi-scale ordered information systems are introduced.With reference to the notion of scale combinations in inconsistent generalized decision multi-scale ordered information systems,representations of information granules as well as lower and upper approximations of sets under different scale combinations are presented and their relationships are examined.With different scales of decisions,several types of optimal scale combinations in inconsistent generalized decision multi-scale ordered information systems are further defined and their relationships are clarified.Finally,a method of discernibility matrix attribute reduction and rule acquisition based on generalized dominance decision functions are explored.

关 键 词：证据理论 多尺度序信息系统 尺度选择 粗糙集 粒计算 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]