%0 Journal Article
%T A neuro-fuzzy method for predicting the chaotic time series<br>一种预测混沌时间序列的模糊神经网络方法
%A Hu Yu-Xia
%A Gao Jin-Feng
%A <br>胡玉霞
%A 高金峰
%J 物理学报
%D 2005
%I 
%X A neuro-fuzzy approach based on a novel hybrid learning method is presented, which can generate the best fuzzy rule set automatically from the desired input-output data pairs only and can give the initial neuro-fuzzy system and the initial parameters of fuzzy membership functions. Then the parameters of fuzzy membership functions and the weights can be easily tuned by employing neural network's self-learning techniques. This approach reduces the rule matching time and accelerates the speed of the fuzzy logic referencing and improves the adaptability of the neuro-fuzzy system. Using the proposed neuro-fuzzy system and the learning algorithms we simulated the prediction of the Lorenz chaotic time series, the results demonstrate the effectiveness of the chaotic time series prediction approach.
%K neuro-fuzzy network
%K fuzzy rules extraction
%K chaotic time series prediction<br>模糊神经网络，
%K 模糊规则提取，
%K 混沌时间序列预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=1FB1610DF69D7D06&yid=2DD7160C83D0ACED&vid=318E4CC20AED4940&iid=708DD6B15D2464E8&sid=B43FFDACD542943E&eid=64A26B45B3348B81&journal_id=1000-3290&journal_name=物理学报&referenced_num=5&reference_num=12