An Investigation on Evolutionary Identification of Continuous Chaotic Systems

Abstract

This paper discusses the possibility of using evolutionary algorithms for the reconstruction of chaotic systems. The main aim of this work is to show that evolutionary algorithms are capable of the reconstruction of chaotic systems without any partial knowledge of internal structure, i.e. based only on measured data. Algorithm SOMA was used in reported experiments here. Systems selected for numerical experiments here is the well-known Lorenz system. For each algorithm and its version, repeated simulations were done, totaling 20 simulations. According to obtained results it can be stated that evolutionary reconstruction is an alternative and promising way as to how to identify chaotic systems.

Identification of Unknown Parameters and Orders via Cuckoo Search Oriented Statistically by Differential Evolution for Noncommensurate Fractional-Order Chaotic Systems

“…. , ) with the non-Lyapunov methods, they are mainly from symbolic regression through genetic programming (GP) [49][50][51], and some are from evolutionary algorithms [52][53][54][55][56][57][58][59][60][61][62].…”