Evaluation on various forecasting models using artificial neural networks (ANN)

Forecasting is the process of estimating or predicting the future. In recent years there is a widespread of interest in establishing a forecasting method that based on phenomenological description and computerized model. Various forecasting techniques have been developed using probabilistic, statistics, simulation or artificial intelligence. The focus of this paper is to review examples of forecasting model using Artificial Neural Networks (ANN). The accuracy of the models was also compared with Power Model, Box-Jenkins approach and Multiple Loglinear Regression. This paper also include a summary on various forecasting models using ANN. Through this study, it was found that forecasting model using ANN approach yield better results than other techniques.