Investigation on unconventional synthesis of astroinformatic data classifier powered by irregular dynamics

Abstract

This paper discusses the mutual combination of the unconventional algorithm (in this case evolutionary algorithms), deterministic chaos and modeling on real data from astrophysics. Analytical programming with selected evolutionary algorithm is used to synthesize suitable models. The main attention in this paper is focused on various chaotic generators, which are used instead of classical pseudo-random number generators. Chaotic generators are used in conjunction with a special case - a generator based on a strange non-chaotic attractor. The performance of all chaotic and non-chaotic based generators is then mutually compared at the end.