This review highlights advancements in mathematical modeling and machine learning for optimizing biogas production, indicating future research opportunities.
Key Points
Recent advancements in mathematical modeling and machine learning enhance biogas production from anaerobic digestion.
Key models evaluated include first-order kinetics and hybrid AI-based models, focusing on their applicability in real-world scenarios.
Artificial neural networks are integrated to optimize biogas yield and address uncertainties in anaerobic digestion processes.
The review identifies research gaps that challenge the robustness of hybrid models and the need for real-time monitoring systems.