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This study suggests a new data-driven model for the prediction of geomagneticstorm. The model which is an instance of Brain Emotional Learning InspiredModels (BELIMs), is known as the Brain Emotional Learning-based PredictionModel (BELPM). BELPM consists of four main subsystems; the connection betweenthese subsystems has been mimicked by the corresponding regions of theemotional system. The functions of these subsystems are explained usingadaptive networks. The learning algorithm of BELPM is defined using thesteepest descent (SD) and the least square estimator (LSE). BELPM is employedto predict geomagnetic storms using two geomagnetic indices, Auroral Electrojet(AE) Index and Disturbance Time (Dst) Index. To evaluate the performance ofBELPM, the obtained results have been compared with ANFIS, WKNN and otherinstances of BELIMs. The results verify that BELPM has the capability toachieve a reasonable accuracy for both the short-term and the long-termgeomagnetic storms prediction.

Brain Emotional Learning-based Prediction Model For the Prediction of Geomagnetic Storms