Example: Modeling Dynamical Systems
- LSTMs can learn complex time evolution of physical systems (e.g. Lorenz attractor, fluid dynamics) from data.
- Serve as data-driven surrogates for ODE/PDE solvers (trained on RK4-generated time series).
- For example, an LSTM surrogate accurately forecast 36h lake hydrodynamics (velocity, temperature) with \( < 6\% \) error.
- Such models dramatically speed up predictions compared to full numerical simulation.