Abstract
The future generation of sustainable and renewable energy may greatly benefit from expanding and implementing biofuel conversion technologies. However, it is challenging to create models centered on experience or theoretical data for precise projections due to the complexity of bioenergy systems and the limits of human computation. Machine learning (ML) and recent advancements in data science may open up new possibilities. This critical chapter offers a thorough understanding of the use of ML in the context of bioenergy. The most recent developments in ML-assisted bioenergy technologies, including lignocellulosic biomass energy conversion and biofuel conversion and applications, are presented. Furthermore, we emphasize the potential and capabilities of sophisticated ML techniques when dealing with various tasks in advancing a new generation of bioenergy and biofuel conversion technologies.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Advances in Lignocellulosic Biofuel Production Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
