Machine learning methods often work as black boxes and do not provide insight of the physics underlying the model. However, a hybrid approach combining physical models with machine learning preserves the physical information, while still improving the flexibility and precision of the model. This type of individually tailored hybrid approach requires a combination of strong domain knowledge and machine learning expertise, but results in robust semi-interpretable models and increased physical understanding.
Hybrid modelling
Combining machine learning with physical models may give the best from both worlds.