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In a special case of type-2 fuzzy logic systems (FLS), i.e. geometric inteIval type-2 fuzzy logic systems (GIT-2FLS), the crisp output is obtained by computing the geometric center of footprint of uncertainly (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. 相似文献
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