Physics-Informed and Data-Driven Forecasting of Chaotic Dynamics Across Lorenz and Rössler Systems
Reliable finite-horizon forecasting of chaotic dynamics is challenging because small approximation errors grow rapidly during recursive prediction. This study presents a controlled comparison of data-driven and physics-regularized forecasting methods for the Lorenz and Rössler systems. The proposed Hybrid Physics-Infor...