基于广义概念格的广义粗近似空间中规则的发现与提取  

Extract Rule from Generalized Rough Approximate Space Based on Generalized Concept Lattice

作　　者：张倩生[1] 周作领[2] 许绍元[1] 贾保果[1] 罗俊[1] 

机构地区：[1]中山大学数学与计算科学学院 [2]中山大学岭南学院,广州510275

出　　处：《计算机科学》2003年第6期133-135,共3页Computer Science

基　　金：国家自然科学基金(10171116);教育部博士点基金(1999055810);广东省自然科学基金(011221)资助

摘　　要：This paper proposes a new method of constructing generahzed concept lattice and producing rules from it in the generalized rough approximate space based on generalized similar relation which is more extensive than equivalent relation. Finally, a simple algorithm is presented to extract rules based on interesting measure.This paper proposes a new method of constructing generalized concept lattice and producing rules from it in the generalized rough approximate space based on generalized similar relation which is more extensive than equivalent relation. Finally, a simple algorithm is presented to extract rules based on interesting measure.

关 键 词：粗集理论 广义概念格 广义粗近似空间 规则提取 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]