Prediction of solar conditions by emotional learning

The increased dependence of human life-world on earth upon orbiting satellites and the threat of solar events that could cause serious damage have triggered a new surge of space weather forecasting research. In this paper, we propose a physiologically motivated prediction methodology for trading off general precision with improved predictive performance in regions of higher interest. Results are compared to very accurate forecasts of ground based geomagnetic activity index (K) and sunspot number obtained by a neuro-fuzzy technique. It has been shown that we can design powerful alert system by using computationally intelligent forecasting techniques.