Strange Nonchaotic Attractors in Evolutionary Processing of Astroinformatic Big Data

In this paper are used evolutionary algorithms on models synthesis, based on real astrophysical data sets. Data used in this paper are from a robotic telescope, Czech Republic, and selected evolutionary algorithms with so-called analytical programming are used to synthesize suitable models that fit measured data. This paper is an extension of our previous research with such difference that so-called strange nonchaotic attractors are used here instead of classical pseudo-random number generators inside used evolutionary algorithms. Results are discussed at the end.

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