基于粗糙集方法的概念格理论研究综述  

A Survey for Study on Concept Lattice Theory via Rough Set

作　　者：仇国芳[1] 张志霞[1] 张炜[1] 

机构地区：[1]西安建筑科技大学管理学院,陕西西安710055

出　　处：《模糊系统与数学》2014年第1期168-177,共10页Fuzzy Systems and Mathematics

基　　金：陕西省自然科学基金资助项目(2011JM9003);教育部人文社科基金资助项目(12YJA630019);管理科学与工程陕西省重点学科建设项目(E08001)

摘　　要：概念格与粗糙集理论是软计算领域的两种不同方法,它们都在数据挖掘、知识工程、信息检索、人工智能、系统分析与管理决策等领域有重要应用。在介绍概念格基本概念的基础上,对近年来借助粗糙集方法研究概念格的粗糙集近似扩充、概念格的约简理论与方法、变精度概念格及基于概念格的模糊推理、概念粒计算系统的数学模型及迭代算法等方面进行了综述,并提出了进一步研究的问题和方向。Concept lattice and rough set theory are two different methods of soft computing, there are important applications in data mining, knowledge engineering, information retrieval, artificial intelligence, system analysis and management decision and other fields. Based on introducing the basic concepts of concept lattice, using the method of rough set theory, extended concept lattice by rough approximations, reduction theory and method of concept lattice, variable precision concept lattice and fuzzy inference based on concept lattice, mathematical model of concept granular computing system and iterative algorithms are reviewed. The further research issues and directions are proposed.

关 键 词：概念格 模糊概念格 变精度概念格 模糊推理 约简 粒计算 

分 类 号：O236[理学—运筹学与控制论] TP391[理学—数学]