PSO type-reduction method for geometric interval type-2 fuzzy logic systems |
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Authors: | ZHAO Xian-zhang GAO Yi-bo ZENG Jun-fang YANG Yi-ping |
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Affiliation: | 1. Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China;China Agricultural University, Beijing 10083, China 2. Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China |
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Abstract: | In a special case of type-2 fuzzy logic systems (FLS), i.e. geometric interval type-2 fuzzy logic sys-tems (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 optimiza-tion (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 perform-ance, and is a satisfactory complement for the theory of GIT-2FLS. |
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Keywords: | interval type-2 fuzzy sets PSO algorithm type-reduction |
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