Features:
- Covers the use of machine learning within the context of the processing of advanced biofuel feedstocks for biofuel production.
- Includes larger alcohols, ethers, levulinates, GTL fuels, and furans production using machine learning approach.
- Discusses how machine learning and biomass-based biofuel production can be integrated.
- Reviews sustainability and cost analysis of artificial intelligence-based biofuel production.
- Explores prediction of the potentiality of lignocellulosic biomass for biofuel applications.
This book is aimed at researchers and graduate students in energy and fuels, chemical engineering, and machine learning.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.








