摘要
在复杂的决策环境下 ,不完全信息是不可避免的 .在此情况下 ,专家往往也能给出满意的决策 .因此从不完全的案例中提取有用的模式 ,用于增强智能系统的知识库 ,是具有实际意义的 .粗集是处理不确定信息的有效方法 ,但它通常适用于完全决策表 .论文对粗集理论在不完全信息下进行了初步的拓展 .
Experts often have to make decisions with incomplete information under complicated underground and can give satisfactory solutions. It is, therefore, useful to extract meaningful patterns from incomplete decision tables for enhancing the quality of knowledge base of intelligent systems. As a method for dealing with indefinite information, previous rough set only concerns with complete decision tables. so the extension of rough set is necessary. In the paper, the problem is discussed, which provides theoretical foundation for mining knowledge from incomplete decision tables.
出处
《系统工程学报》
CSCD
2002年第6期481-485,共5页
Journal of Systems Engineering
