| A Multilayer Recurrent Fuzzy Neural Network for Accurate Dynamic System Modeling |
| |
| 作者姓名： | 柳贺 黄道 |
| |
| 作者单位： | School of Information Science and Engineering，East China University of Science and Technology |
| |
| 摘 要： | A multilayer recurrent fuzzy neural network （MRFNN） is proposed for accurate dynamic system modeling. The proposed MRFNN has six layers combined with T-S fuzzy model. The recurrent structures are formed by local feedback connections in the membership layer and the rule layer. With these feedbacks, the fuzzy sets are time-varying and the temporal problem of dynamic system can be solved well. The parameters of MRFNN are learned by chaotic search （CS） and least square estimation （LSE） simultaneously, where CS is for tuning the premise parameters and LSE is for updating the consequent coefficients accordingly. Results of simulations show the proposed approach is effective for dynamic system modeling with high accuracy.
|
| 关 键 词： | 循环神经网络 T-S模糊模式 最小二乘方估值 建模 |
A Multilayer Recurrent Fuzzy Neural Network for Accurate Dynamic System Modeling |
| |
| LIU He,HUANG Dao.A Multilayer Recurrent Fuzzy Neural Network for Accurate Dynamic System Modeling[J].Journal of Donghua University,2008,25(4):373-378. |
| |
| Authors: | LIU He HUANG Dao |
| |
| Institution: | School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China |
| |
| Abstract: | A multilayer recurrent fuzzy neural network(MRFNN)is proposed for accurate dynamic system modeling.The proposed MRFNN has six layers combined with T-S fuzzy model.The recurrent structures are formed by local feedback connections in the membership layer and the rule layer.With these feedbacks,the fuzzy sets are time-varying and the temporal problem of dynamic system can be solved well.The parameters of MRFNN are learned by chaotic search(CS)and least square estimation(LSE)simultaneously,where CS is for tuning the premise parameters and LSE is for updating the consequent coefficients accordingly.Results of simulations show the proposed approach is effective for dynamic system modeling with high accuracy. |
| |
| Keywords: | recurrent neural networks T-S fuzzy model chaotic search least square estimation modeling |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
