基于粗糙集合理论的知识发现综述  

KNOWLEDGE DISCOVERY BASED ON ROUGH SET THEORY:A SURVEY

作　　者：王志海[1] 胡可云[1] 胡学钢[1] 徐本柱[1] 刘宗田[1] 张奠成[1] 

机构地区：[1]合肥工业大学计算机与信息学院人工智能应用研究室,230009

出　　处：《模式识别与人工智能》1998年第2期176-183,共8页Pattern Recognition and Artificial Intelligence

基　　金：国家教委博士点专项科研基金;安徽省自然科学基金

摘　　要：粗糙集合理论是一种新的处理模糊和不确定性的数学工具,它已经应用于机器学习、知识发现、决策支持系统和模式识别等领域.本文阐述了粗糙集合理论的基本思想与特点,介绍了知识发现的一般过程.重点评述了基于粗糙集合理论的知识发现方法,介绍了几个基于粗糙集合理论的典型系统.Rough Set, theory is a new mathematical tool to deal with vagueness and uncertainty. It has been used in machine learning, knowledge discovery, decision support systems, and pattern recognition. In this paper, we explain the basic idea and characteristics of Rough Set theory, introduce the general procedure of knowledge discovery in databases. Then, we mainly review the knowledge discovery methods based on Rough Set theory, which extended the original Rough Set theory, or combined with other related tools. Finally, we analyze several representative systems based on Rough Set theory.

关 键 词：粗糙集合 知识发现 机器学习 人工智能 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]