Parameter Estimation of Loranz Chaotic Dynamic System Using Bees Algorithm

Abstract

An important problem in nonlinear science is the unknown parameters estimation in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Bees algorithm (BA) is a new member of meta-heuristics. BA tries to model natural behavior of honey bees in food foraging. This paper focuses on using the BA to solve this problem. Simulation results demonstrate the merit, effectiveness and robustness of BA.