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Nonlinear Time Series Prediction Using Chaotic Neural Networks 被引量:3
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作者 LIKe-Ping CHENTian-Lun 《Communications in Theoretical Physics》 SCIE CAS CSCD 2001年第6期759-762,共4页
A nonlinear feedback term is introduced into the evaluation equation of weights of the backpropagation algorithm for neural network, the network becomes a chaotic one. For the purpose of that we can investigate how th... A nonlinear feedback term is introduced into the evaluation equation of weights of the backpropagation algorithm for neural network, the network becomes a chaotic one. For the purpose of that we can investigate how the different feedback terms affect the process of learning and forecasting, we use the model to forecast the nonlinear time series which is produced by Makey-Glass equation. By selecting the suitable feedback term, the system can escape from the local minima and converge to the global minimum or its approximate solutions, and the forecasting results are better than those of backpropagation algorithm. 展开更多
关键词 neural network chaotic dynamics forecasting nonlinear time series
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