An Improved Model of Brain Emotional Learning Algorithm Based on Interval Knowledge

The brain emotional learning algorithm inspired by a reduced system of a computational model simulates the brain learning performance quite simply with mimicking mammalian brains. The present paper endeavors to come forward to an improved model of the emotional learning algorithm based on the interval knowledge. In this proposed model, based on the interval knowledge, the weights of the amygdala and orbitofrontal sections will be updated. Eventually, the results of implementing and performing the improved brain emotional learning algorithm will be presented to be compared with the original version of the algorithm to Prediction the chaotic time series, Lorenz and Rossler, about which a noticeable improvement in its precision, accuracy and speed of convergence of the final results is reported.