A Brain Emotional Learning-based Prediction Model A Brain Emotional Learning-based Prediction Model For the Prediction of Geomagnetic Storms
Mahboobeh Parsapoor, Urban Bilstrup, Bertil Svensson
Citation: Proceedings of the 2014 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 2, pages 35–42 (2014)
Abstract. This study suggests a new data-driven model for the prediction of geomagnetic storm. The model is known as the Brain Emotional Learning-based Prediction Model (BELPM). BELPM consists of four main subsystems; the connection between these subsystems has been mimicked by the corresponding regions of the emotional system. The functions of these subsystems are explained using adaptive networks. The learning algorithm of BELPM is defined using the steepest descent (SD) and the least square estimator (LSE). BELPM is employed to predict geomagnetic storms using two geomagnetic indices, Auroral Electrojet (AE) Index and Disturbance Time (Dst) Index. To evaluate the performance of BELPM, the obtained results have been compared with ANFIS, WKNN. The results verify that BELPM has the capability to achieve a reasonable accuracy for both the short-term and the long-term geomagnetic storms prediction.