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F. Mohamed

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Open access Jul 2026

Predicting Chaotic Attractor Dynamics in the Rössler System Using Deep Neural Networks: Influence of Initial Conditions and Forcing Parameters

This study investigates the capability of deep neural networks to infer the time-evolution of the Rössler system a canonical chaotic oscillator by leveraging initial conditions and forcing parameters as input variables and underscores the need for hybrid approaches to address long-term instability.

A. Fateh, Harrag Abdelmalek, F. Mohamed et al. · 0 citations