Open access
Aug 2026
Chaos Prediction: Machine Learning Versus Dynamical Models
This work uses error-free computation of two isomorphic chaotic systems, namely the Logistic map and the Tent map, to investigate the ability of Echo State Networks (ESNs) to learn and predict chaos, suggesting that ESNs exhibit significantly different predictive performance on the two isomorphic dynamical systems.
Alexandros K. Angelidis, Georgios C. Makris, E. Ioannidis et al.
· Mathematics · 0 citations