基于变精度粗糙直觉模糊集的决策规则获取

以直觉模糊目标信息系统为研究对象，以粗糙集和直觉模糊集为工具，以知识发现为目的，给出了从直觉模糊决策表中获取决策规则的一种有效方法。即通过对Pawlak粗糙隶属函数的定义进行推广，给出粗糙直觉模糊隶属函数，利用新的粗糙隶属函数，建立了变精度粗糙直觉模糊集模型。在此模型基础上定义了变精度粗糙直觉模糊集的近似质量和近似约简，由近似约简导出概率决策规则集，从而给出了直觉模糊决策表的概率决策规则获取方法。最后，以实例说明了这一方法的有效性。关键词：

Decision rule acquisition based on variable precision rough intuitionistic fuzzy sets

Taking the intuitionistic fuzzy goal information system as the research object, rough set and intuitionistic fuzzy sets as the research tools, knowledge discovery as the research purpose, an effective method is given to get decision rules from the intuitionistic fuzzy decision table. That is, through generalizing the definition of Pawlak rough membership functions, the rough intuitionistic fuzzy membership function is given, and using new rough membership function, a variable precision rough intuitionistic fuzzy set model is established. And based on this model, the approximation quality and approximate reduction of the variable precision rough intuitionistic fuzzy set are defined, the approximate reduction derives the probabilistic decision rules set, hence the probabilistic decision rules of the intuitionistic fuzzy decision table acquisition method is given. Finally, the practical example is given to illustrate the effectiveness of the method.