Emotional Brain-Inspired Adaptive Fuzzy Decayed Learning for Online Prediction Problems

In this paper, we propose a Fuzzy Adaptive Brain-Inspired Emotional Decayed Learning named Fuzzy ADBEL. Fuzzy ADBEL is a computational model that models the forgetting process and inhibitory mechanism of the emotional brain. In the model, the fuzzy decay rate simulates the forgetting process, and the stimulus and learning weights are considered as fuzzy variables trained by fuzzy learning rules. The final output of the model is evaluated by a fuzzy decision making layer that simulates the inhibitory mechanism. The proposed Fuzzy ADBEL is utilized to predict the Kp, AE and Dst indices showing opposite behaviors and characterizing the chaotic activity of the earth's magnetosphere. Experimental results show that fuzzy approaches including Fuzzy ADBEL and ANFIS (Adaptive NeuroFuzzy Inference System) reaches steady state faster than non-fuzzy approaches, ADBEL and MLP (Multilayer Perceptron). Hence, we hope the proposed model can be used in real time chaotic time series prediction.