Applications of improved grey prediction model for power demand forecasting

Grey theory is a truly multidisciplinary and generic theory that deals with systems that are characterized by poor information and/or for which information is lacking. In this paper, an improved grey GM(1,1) model, using a technique that combines residual modification with artificial neural network sign estimation, is proposed. We use power demand forecasting of Taiwan as our case study to test the efficiency and accuracy of the proposed method. According to the experimental results, our proposed new method obviously can improve the prediction accuracy of the original grey model