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- W2384689903 abstract "According to the theories of adaptive fuzzy logic system and general parameter optimization, the characteristics of normal parameter-learning algorithms on fuzzy logic systems are firstly analyzed, and its some defects are discussed briefly. Aimed at improving parameter-training pace, a new adaptive parameter-learning algorithm is then advanced, which is deduced and explained in detail. Lastly, the proposed algorithm has been evaluated by a nonlinear function to approximate its ideal values; system抯 simulation precision and its rate of convergence are enhanced remarkably. Those results demonstrate the efficiency and feasibility of the proposed adaptive optimization algorithm, which can overcome some deficiencies of normal parameter-learning algorithms." @default.
- W2384689903 created "2016-06-24" @default.
- W2384689903 creator A5032573816 @default.
- W2384689903 date "2004-01-01" @default.
- W2384689903 modified "2023-09-26" @default.
- W2384689903 title "An Adaptive Parameters Learning Algorithm for Fuzzy Logic Systems" @default.
- W2384689903 hasPublicationYear "2004" @default.
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