頁籤選單縮合
題名 | Development of a Self-Organized Neuro-Fuzzy Model by Using Genetic Algorithm for System Identification= |
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作者 | Chen, Chuen-jyh; Yang, Shih-ming; Lin, Shih-guei; |
期刊 | Journal of Aeronautics, Astronautics and Aviation. Series A |
出版日期 | 20141200 |
卷期 | 46:4 2014.12[民103.12] |
頁次 | 頁281-289 |
分類號 | 447.5 |
語文 | eng |
關鍵詞 | Neuro-fuzzy system; Genetic algorithms; System identification; |
英文摘要 | In neuro-fuzzy applications, it is known that the selections in neural network structure, fuzzy logic membership functions, and fuzzy logic rules are very challenging as they are sensitive to modeling accuracy. A neuro-fuzzy model with genetic algorithm is developed for system identification, where fuzzy logic is to tune the membership functions by three-phase learning and genetic algorithm is to search the optimal parameters of the model. The weight/bias in artificial neural network, the center/width of membership function, and the fuzzy logic rules can all be determined. Performance verification of system identification by a benchmark nonlinear difference equation shows that the neuro-fuzzy model with genetic algorithm is most effective in modeling accuracy. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。