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Chaos and artificial neural networks have been providing a new rout for investigating the complicated nonlinear time series. As the traditional neural networks are easy to get slow convergence and produce large redundancy which might consequently bring low efficiency, the biased wavelet neural networks is employed to build chaotic time series forecasting. Efforts are also made to assess the forecast...
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