Explore the potential of hybrid AI in oil and gas and other process industries, and learn how combining physics with machine learning delivers working AI for industry.
In this webinar, we will present two use cases for what’s known as physics-guided ML or hybrid AI: An oil-in-water prediction, root cause analysis, and preventive action system and transferring lessons from oil and gas to industries that produce goods such as cement, paint, and fish oil.
- Combining physics-based modeling and machine learning
- Fit for industrial systems analysts across a range of scenarios
- Subject-matter and data science requirements
- Why semi-interpretable prediction logic is preferred
- Cost efficiency compared to pure physics-modeling in production and at scale across fleets of assets
- Machine learning training with synthetic data
