Decomposed neuro-fuzzy ARX model

Abstract

This paper explores a new approach for the modelling and identification of non-linear dynamic systems. A model, named the Decomposed Neuro- Fuzzy Auto-Regressive with eXogenous input model (DNFARX), based on decomposed structure of the fuzzy inference system, is proposed. An evolution of a neural network learning algorithm for the decomposed structure of the fuzzyinference system is suggested. A comparative study of the dynamic system modelling with conventional fuzzy inference system based models and the proposed model is presented for Box-Jenkins data set.