An Interactively Recurrent Functional Neural Fuzzy Network with Fuzzy Differential Evolution and its Applications

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题名:	An Interactively Recurrent Functional Neural Fuzzy Network with Fuzzy Differential Evolution and its Applications
作者:	CHENG-JIAN LIN, CHIH-FENG WU,HSUEH-YI LIN & CHENG-YI YU
贡献者:	圖書館
关键词:	Control differential evolution neural fuzzy network prediction recurrent network
日期:	2015
上传时间:	2016-10-20 14:48:35 (UTC+8)
摘要:	In this paper, an interactively recurrent functional neural fuzzy network (IRFNFN) with fuzzy differential evolution (FDE) learning method was proposed for solving the control and the prediction problems. The traditional differential evolution (DE) method easily gets trapped in a local optimum during the learning process, but the proposed fuzzy differential evolution algorithm can overcome this shortcoming. Through the information sharing of nodes in the interactive layer, the proposed IRFNFN can effectively reduce the number of required rule nodes and improve the overall performance of the network. Finally, the IRFNFN model and associated FDE learning algorithm were applied to the control system of the water bath temperature and the forecast of the sunspot number. The experimental results demonstrate the effectiveness of the proposed method.
關聯:	Sains Malaysiana 44(12)(2015): 1721–1728
显示于类别:	[資訊工程系(所)] 【資訊工程系所】期刊論文

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