Soft computing approach to nonlinear system identification
Shigeyasu Kawaji, Y. Chen · 2002
This paper is concerned with the identification of nonlinear systems by utilizing soft computing approaches. A uniformly framework for evolving the basis function,networks is proposed. The used soft computing technologies including probabilistic incremental program evolution algorithm, (PIPE), artificial neural networks (ANNs), fuzzy systems and random search algorithm.. Simulation results for the identification, of nonlinear systems show the feasibility and effectiveness of the proposed method.