Architecture design of artificial neural networks based on Box & Jenkins models for time series prediction

Abstract

This paper reports the results of a neural architecture design approach for time series prediction. This approach applies some concepts of the Box-Jenkins (1970) method for data preprocessing and network design. The data used to verify the performance of these approaches were stock market time series of the Brazilian telecommunication company TELEBRAS.