  Solar activity It is vital to accurately predict solar activity, in order to
decrease the plausible damage of electronic equipment in the event of a large
high-intensity solar eruption. Recently, we have proposed BELFIS (Brain
Emotional Learning-based Fuzzy Inference System) as a tool for the forecasting
of chaotic systems. The structure of BELFIS is designed based on the neural
structure of fear conditioning. The function of BELFIS is implemented by
assigning adaptive networks to the components of the BELFIS structure. This
paper especially focuses on performance evaluation of BELFIS as a predictor by
forecasting solar cycles 16 to 24. The performance of BELFIS is compared with
other computational models used for this purpose, and in particular with
adaptive neuro-fuzzy inference system (ANFIS).
