直觉模糊语义匹配的相似性度量

首先引用Atanassov直觉模糊集的基本概念和运算，综合考虑其隶属度函数与非隶属度函数两个因素的影响，通过对Zadeh模糊集相似度的计算模型进行扩展，给出了直觉模糊语义匹配的相似度的几种扩展计算方法，即最大最小法、算术平均最小法、几何平均最小法、相关系数法、指数法等，并举例阐明其应用，从而使直觉模糊语义匹配度的计算方法得到进一步拓广。最后，研究了直觉模糊相似关系，证明了直觉模糊相似矩阵的一个定理。

intuitionistc fuzzy sets; fuzzy logic; semantic matching; similarity

The fundamental notions and operations on Atanassov's Intuitionistic Fuzzy Sets are first introduced. Several extended techniques, i.e. those of max-min, arithmetic mean minimum, geometric mean minimum, correlative moduli and correlative exponents, for calculating the similarity on semantic match for intuitionistic fuzzy are proposed by making extensions of models for calculating similarity on Zedeh fuzzy sets with the emphasis on consideration of the effects of both the membership and the nonmembership. The applications are illustrated with examples, which further develops the approaches to calculating semantic matching degree on the intuitionistic fuzzy sets as an extension. Finally, intuitionistic fuzzy relations are investigated with the proof of a theorem on intuitionistic fuzzy similar matrix.