Abstract
To solve prediction of sunspot number, a parallel process neural networks model is proposed in this paper, Firstly, by dividing the whole time-varying process into several small time intervals, the process neural networks are constructed in these small time intervals, which may disperse the load of networks. Then, employing the orthogonal basis expansion in functional space, the learning algorithm of the above-mentioned model is designed. The experimental results of time series predication of sunspots show that the proposed method has great potential for complicated nonlinear time series prediction.
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