New method for design of fuzzy systems for nonlinear modelling using different criteria of interpretability

Abstract

In this paper a new method for designing neuro-fuzzy systems for nonlinear modelling is proposed. This method contains a complex weighted fitness function with interpretability criteria and new enhanced tuning process for selecting parameters and structure of the system based on a hybrid population-based algorithm (composed of evolutionary strategy, genetic algorithm and bees algorithm). To evaluate this method, we used a well-known dynamic nonlinear modelling problem. © 2014 Springer International Publishing.