Artificial intelligence for waste management in smart cities: a review
The rising amount of waste generated worldwide is inducing issues of pollution, waste
management, and recycling, calling for new strategies to improve the waste ecosystem, such …
management, and recycling, calling for new strategies to improve the waste ecosystem, such …
[HTML][HTML] Machine-learning-aided thermochemical treatment of biomass: a review
H Li, J Chen, W Zhang, H Zhan, C He… - Biofuel Research …, 2023 - biofueljournal.com
Thermochemical treatment is a promising technique for biomass disposal and valorization.
Recently, machine learning (ML) has been extensively used to predict yields, compositions …
Recently, machine learning (ML) has been extensively used to predict yields, compositions …
Applications of machine learning in thermochemical conversion of biomass-A review
Thermochemical conversion of biomass has been considered a promising technique to
produce alternative renewable fuel sources for future energy supply. However, these …
produce alternative renewable fuel sources for future energy supply. However, these …
Machine learning for hydrothermal treatment of biomass: A review
W Zhang, Q Chen, J Chen, D Xu, H Zhan, H Peng… - Bioresource …, 2023 - Elsevier
Abstract Hydrothermal treatment (HTT)(ie, hydrothermal carbonization, liquefaction, and
gasification) is a promising technology for biomass valorization. However, diverse variables …
gasification) is a promising technology for biomass valorization. However, diverse variables …
Machine learning predicts and optimizes hydrothermal liquefaction of biomass
The hydrothermal liquefaction process has recently attracted more attention in biorefinery
design and implementation because of its capability of handling various wet biomass …
design and implementation because of its capability of handling various wet biomass …
Recent advances and future prospects of thermochemical biofuel conversion processes with machine learning
Biofuels have been widely recognized as potential solutions to addressing the climate crisis
and strengthening energy security and sustainability. However, techno-economic and …
and strengthening energy security and sustainability. However, techno-economic and …
Machine learning prediction and optimization of bio-oil production from hydrothermal liquefaction of algae
W Zhang, J Li, T Liu, S Leng, L Yang, H Peng… - Bioresource …, 2021 - Elsevier
Hydrothermal liquefaction (HTL) of algae is a promising biofuel production technology.
However, it is always difficult and time-consuming to identify the best optimal conditions of …
However, it is always difficult and time-consuming to identify the best optimal conditions of …
[HTML][HTML] Interpretable machine learning to model biomass and waste gasification
Abstract Machine learning has been regarded as a promising method to better model
thermochemical processes such as gasification. However, their black box nature can limit …
thermochemical processes such as gasification. However, their black box nature can limit …
Machine learning methods for modeling conventional and hydrothermal gasification of waste biomass: A review
Conventional and hydrothermal gasification are promising thermochemical technologies for
the production of syngas from waste biomass. Both gasification processes are complex, with …
the production of syngas from waste biomass. Both gasification processes are complex, with …
Wet wastes to bioenergy and biochar: A critical review with future perspectives
The ever-increasing rise in the global population coupled with rapid urbanization demands
considerable consumption of fossil fuel, food, and water. This in turn leads to energy …
considerable consumption of fossil fuel, food, and water. This in turn leads to energy …