An investigation on evolutionary reconstruction of continuous chaotic systems

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 and a predefined set of basic mathematical “objects”. Algorithm SOMA and differential evolution were used in reported experiments here. Systems selected for numerical experiments here is the well-known Lorenz system, Simplest Quadratic Flow, Double Sroll, Damped Driven Pendulum and Nosé—Hoover oscillator. For each algorithm 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.