基于区间值相似度的直觉区间值模糊推理

Intuitionistic Interval Value Fuzzy Reasoning Based on Interval Value Similarity Measure

直觉区间值模糊集具有比直觉模糊集更强大的模糊信息表达能力并且其直觉区间值隶属度和非隶属度的值较易确定.文章利用直觉区间值模糊集进行模糊推理.根据直觉区间值隶属度和非隶属度的值给出直觉区间值模糊集之间相似度和加权总体相似度的计算方法.根据该计算方法给出直觉区间值模糊集上的模糊推理算法.最后通过算例说明所给出的推理算法更符合实际需要,可操作性强,便于应用.

Intuitionistic interval valued fuzzy set has more powerful ability to represent fuzzy information than intuitionistic fuzzy sets and the intuitionistic interval-valued membership and non membership value of which is easy to detemaine. The intuitionistic interval valued fuzzy set is used to fuzzy inference in the paper. According to the intuitionistic interval valued membership and non membership value, a calculation method of similarity measure and weighted overall similarity between intuitionistic interval valued fuzzy set is proposed. Based on this calculation method, a fuzzy reasoning algorithm on the intuitionistic interval valued fuzzy set is introduced. Finally, an example is illustrated to show the proposed resasoning algorithm is more consistent with the actual needs, strong operability and convenient for application