Prediction of solar conditions by emotional learning

Article type: Research Article

Authors: Babaie, T.^{a; *} | Karimizandi, R.^a | Lucas, C.^{b; c}

Affiliations: [a] Center of Excellence for Control and Intelligent Processing, Electrical and Computer Engineering Department, Faculty of Engineering, University of Tehran, P.O. Box: 11365–4563, Tehran, Iran | [b] Center of Excellence for Control and Intelligent Processing, Electrical and Computer Engineering Department Faculty of Engineering, University of Tehran, Tehran, Iran. P.O. Box: 11365–4563 | [c] School of Intelligent Systems, Institute for studies in theoretical Physics and Mathematics, P.O. Box: 19395–5746, Tehran, Iran

Correspondence: [*] Corresponding author: Tahereh Babaie, NO. 18, 19th Eastern St, Sarrafha Ave, Darya Blvd, Saadat Abad, Tehran, Iran. Tel.: +98 21 8866 5232; E-mail: t.babaie@ece.ut.ac.ir.

Abstract: 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.

Keywords: Brain emotional learning, prediction, solar activity

DOI: 10.3233/IDA-2006-10607

Journal: Intelligent Data Analysis, vol. 10, no. 6, pp. 583-597, 2006