關鍵字查詢 | 類別:會議論文 | | 關鍵字:A Real-Valued GA-Based Approach to Extracting Control Fuzzy Rules

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序號 學年期 教師動態
1 84/2 電機系 蘇木春 教授 會議論文 發佈 A Real-Valued GA-Based Approach to Extracting Control Fuzzy Rules , [84-2] :A Real-Valued GA-Based Approach to Extracting Control Fuzzy Rules會議論文A Real-Valued GA-Based Approach to Extracting Control Fuzzy RulesSu, Mu-Chun; Chang, Hsiao-Te; Yu, Hua-Chiao淡江大學電機工程學系遺傳演算法;模糊邏輯控制器;神經-模糊系統;專家系統;Genetic Algorithm;Fuzzy Logic Controller;Neuro-Fuzzy System;Expert System一九九六自動控制研討會暨兩岸機電及控制技術交流學術研討會論文集=Proceedings of 1996 Automatic Control Conference,頁289-294淡江大學; 自動控制學會; 教育部In this paper, we present a neuro-fuzzy approach to design a controller directly from numerical data. The proposed neuro-fuzzy system is implemented as a two-layer Fuzzy Degraded HyperEllipsoidal Composite Neural Network(FDHECNN). We used a real-valued genetic algorithm to adjust weights of the composite neural networks. After sufficient training, the synaptic weights of the trained FDHECNN can be utilized to extract a set of fuzzy if-then rules. The performance of a trained FDHECNN is shown to be computationally identical to a fuzzy logic controller. The effectiveness and feasibility of the neuro-fu
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