Forecasting Iraqi oil production using artificial neural networks

Abstract

Artificial neural networks (ANNs) are bendy computational structures and yet ordinary approximations as the execute stand applied to day selection predicting especially correct problems. The paper aims to address the effect on the outputs of Artificial Neural Network of the number of input layer nodes, and to minimize error. Time series views included the amount of Iraqi oil production for the 2011–2019 period. The most important finding of this paper is the greater the number of artificial neural network inputs, the smaller the error, and the improved performance results, which reflect positively on the prediction results.