In a special case of type-2 fuzzy logic systems(FLS),i.e.geometric interval type-2 fuzzy logic systems(GIT-2FLS),the crisp output is obtained by computing the geometric center of footprint of uncertainty(FOU)without t...In a special case of type-2 fuzzy logic systems(FLS),i.e.geometric interval type-2 fuzzy logic systems(GIT-2FLS),the crisp output is obtained by computing the geometric center of footprint of uncertainty(FOU)without type-reduction,but the defuzzifying method acts against the corner concepts of type-2 fuzzy sets in some cases.In this paper,a PSO type-reduction method for GIT-2FLS based on the particle swarm optimization(PSO)algorithm is presented.With the PSO type-reduction,the inference principle of geometric interval FLS operating on the continuous domain is consistent with that of traditional interval type-2 FLS operating on the discrete domain.With comparative experiments,it is proved that the PSO type-reduction exhibits good performance,and is a satisfactory complement for the theory of GIT-2FLS.展开更多
基金Sponsored by the National Hi-Tech Program of China(Grant No. 2005AA420050)the National Key Technology R&D Program of China(Grant No.2006BAD10A0401, 2006BAH02A01)
文摘In a special case of type-2 fuzzy logic systems(FLS),i.e.geometric interval type-2 fuzzy logic systems(GIT-2FLS),the crisp output is obtained by computing the geometric center of footprint of uncertainty(FOU)without type-reduction,but the defuzzifying method acts against the corner concepts of type-2 fuzzy sets in some cases.In this paper,a PSO type-reduction method for GIT-2FLS based on the particle swarm optimization(PSO)algorithm is presented.With the PSO type-reduction,the inference principle of geometric interval FLS operating on the continuous domain is consistent with that of traditional interval type-2 FLS operating on the discrete domain.With comparative experiments,it is proved that the PSO type-reduction exhibits good performance,and is a satisfactory complement for the theory of GIT-2FLS.
