On using backpropagation for prediction: an empirical study

Abstract

The authors describe the results of initial efforts in applying backpropagation to the prediction of future values of four time series, namely, the sunspot series, a monthly department store sales time series, and two financial index time series. They describe various ways of customizing the backpropagation network for prediction and discuss some experimental results. They also propose a modified learning rule based on optimizing correct predictions of upward and downward trends in a time series.<>