What is hybrid modeling in time series forecasting systems?

Hybrid modeling combines classical statistical models and machine learning models to leverage both linear and nonlinear patterns.

Hybrid models integrate methods like ARIMA for linear structure and neural networks for nonlinear residual learning. The idea is to decompose signal into components and model each with the most suitable technique. This improves accuracy and robustness, especially in complex real-world systems.