智能决策中的模糊近似

信息表通过目标集合来描述，目标通过条件属性和决策属性进行描述，在对这样的信息表分析处理过程中，粗糙集理论是一个非常有用的工具，粗糙集合理论的主要观点就是知识的上下近似，在实际中，条件属性和决策属性的概念通常是模糊的，而且可以利用模糊集合来说明，提出了基于模糊集合和粗糙集结合的一种新方法，对包含度进行了定义，给出了截近似和综合函数的概念，应用这些概念并结合具体例子讨论了条件属性和决策属性之间的关系，为决策过程中对条件属性权值的指定提供了理论基础。

The Concept of Fuzzy Approximation in Decision Making

The rough sets theory proves to be a very useful tool for analysis of information tables which describes objects by means of disjoint subsets of condition and decision attributes The key idea of rough sets is approximation of knowledge expressed by decision attributes using knowledge expressed by condition attributes In real life the decision and condition concepts are often fuzzy and described by fuzzy sets A new method for decision making is proposed, which is derived from the combination of rough sets and fuzzy sets The concept of inclusion degree of fuzzy sets and level approximation and aggregation function are given, and discussing the relationship between condition and decision attributes with some examples This offers theoretical foundation for assigning the weights to condition attributes during decision making