Alejandro Flores-Méndez

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Polynomial artificial neural networks have shown to be a powerful Network for forecasting non linear time series. With this type of networks it is possible to have information about the nature of the time series analyzed. However, the problem with this type of network is the computation time required and sometimes the huge number of terms of the polynomial(More)
The Polynomial Artificial Neural Network (PANN) has shown to be a powerful Network for time series forecasting. Moreover, the PANN has the advantage that it encodes the information about the nature of the time series in its architecture. However, the problem with this type of network is that the terms needed to be analyzed grow exponentially depending on(More)
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