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Solar activity It is vital to accurately predict solar activity, in order todecrease the plausible damage of electronic equipment in the event of a largehigh-intensity solar eruption. Recently, we have proposed BELFIS (BrainEmotional Learning-based Fuzzy Inference System) as a tool for the forecastingof chaotic systems. The structure of BELFIS is designed based on the neuralstructure of fear conditioning. The function of BELFIS is implemented byassigning adaptive networks to the components of the BELFIS structure. Thispaper especially focuses on performance evaluation of BELFIS as a predictor byforecasting solar cycles 16 to 24. The performance of BELFIS is compared withother computational models used for this purpose, and in particular withadaptive neuro-fuzzy inference system (ANFIS).

Forecasting Solar Activity with Two Computational Intelligence Models (A Comparative Study)