Time Series Forecasting Using Computational Intelligence Methods
نویسندگان
چکیده
Abstract: Forecasting the future evolution of a system based only on past information comprises a central scientific problem. In this work we investigate the comparative performance of recurrent multi–layer perceptrons, trained through backpropagation through time and the differential evolution algorithm, to perform one–step–ahead predictions for the laser time series (Data set A) from the Santa–Fe Time Series Prediction and Analysis Competition [1].
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تاریخ انتشار 2004