@conference {Walid2021,
	title = {Modeling and optimization of anaerobic digestion: A review},
	booktitle = {E3S Web of Conferences},
	volume = {229},
	year = {2021},
	note = {cited By 2},
	abstract = {Anaerobic digestion is recognized as being an advantageous waste management technique representing a source of clean and renewable energy. However, biogas production through such practice is complex and it relies on the interaction of several factors including changes in operating and monitoring parameters. Enormous researchers have focused and gave their full attention to mathematical modeling of anaerobic digestion to get good insights about process dynamics, aiming to optimize its efficiency. This paper gives an overview of the different approaches applied to tackle this challenge including mechanistic and data-driven models. This review has led us to conclude that neural networks combined with metaheuristic techniques has the potential to outperform mechanistic and classical machine learning models. {\textcopyright} The Authors, published by EDP Sciences, 2021.},
	keywords = {Anaerobic digestion, Biogas production, Data-driven model, Machine learning models, Management techniques, Meta-heuristic techniques, Modeling and optimization, Monitoring parameters, Optimization, Renewable energies},
	doi = {10.1051/e3sconf/202122901022},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100132508\&doi=10.1051\%2fe3sconf\%2f202122901022\&partnerID=40\&md5=5d2367868bbe9ebe8e867ca9622eda34},
	author = {Walid, F. and El Fkihi, S. and Benbrahim, H. and Tagemouati, H.}
}
