基于区间值t-模的区间值直觉模糊集的截集

Cuts of Interval-valued Intuitionistic Fuzzy Sets Based on Interval-valued t-Norms

拥有更多自由度的区间值直觉模糊集在处理信息的模糊性和不确定性时比经典直觉模糊集更有优势.截集是连接模糊集和经典集的桥梁,研究区间值直觉模糊集的截集有助于我们更灵活地处理区间值直觉模糊集.本文首先定义一种基于区间值t-模的区间值直觉模糊集的截集,进一步借助于区间值t-模的性质,系统地研究基于区间值t-模的区间值直觉模糊集的截集的性质,并给出几个基于区间值t-模的区间值直觉模糊集的截集的基本定理.

Interval-valued intuitionistic fuzzy sets with more degrees of freedom have more advantage on dealing with information which contains fuzziness and uncertainty than classical intuitionistic fuzzy sets. Cut set bridges between fuzzy sets and classical ones. So studying the cuts of interval-valued intuitionistic fuzzy sets could help us to deal with interval-valued intuitionistic fuzzy sets flexibly. In this paper, a definition of cuts of interval- valued intuitionistic fuzzy sets based on interval-~valued t-norm is represented. And then we investigate the property and give some fundamental theorem of cuts of interval-valued intuitionistic fuzzy sets based on interval- valued t-norm underlying the property of interval-valued t-norm.