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In this decade, it is not necessary to have technical knowledge for the investment since the automatic algorithms to sell/buy investment destination have been developed with artificial intelligence (AI). In our previous study, measuring similarity (stationarity, fractality, and degree of determinism) of variations in the exchange rates to the pseudo-exchange rates generated by Generative Adversarial Networks (GANs), we compared Winner processes with the GANs. From the viewpoint of stationarity, the similarity of sequences in the pseudo exchange rates were higher than those generated by the Winner processes, and high scores in the similarity were resulted from both sequences in terms of degree of determinism. In this study, we have applied this AI system to numerical simulations of the stabilogram whose randomness is remarkably greater than that of the other bio-signal in accordance with the nonlinear analysis., source:https://www.springerprofessional.de/en/numerical-analysis-of-bio-signal-using-generative-adversarial-ne/18421228