A biological brain-inspired fuzzy neural network: Fuzzy emotional neural network

Abstract

In this paper, a brain-inspired fuzzy emotional neural network (FUZZ-ENN) is proposed for uncertainty prediction tasks in real world applications. In the proposed FUZZ-ENN, amygdala connections are modeled by fuzzy IF-THEN behavioral rules and orbitofrontal module inhibits the amygdala responses in order to decrease the uncertainty. This computational model is based on the inhibitory connections in the human emotional brain’s nervous system inhibiting the uncertainty. In this paper, genetic algorithm is applied for optimal tuning of crisp numerical and fuzzy parameters of the proposed model. A traditional neural model and a two layered emotional neural network (ENN) are also implemented for comparison purposes on the electrical load and wind power forecasting problem and the prediction of geomagnetic activity indices as two real world case studies. Numerical results indicate the superiority of the proposed approach in term of lower uncertainty in the prediction.