Intelligent approaches for sustainable management and valorisation of food waste
Food waste (FW) is a severe environmental and social concern that today's civilization is
facing. Therefore, it is necessary to have an efficient and sustainable solution for managing …
facing. Therefore, it is necessary to have an efficient and sustainable solution for managing …
Application of machine learning in anaerobic digestion: Perspectives and challenges
Anaerobic digestion (AD) is widely adopted for remediating diverse organic wastes with
simultaneous production of renewable energy and nutrient-rich digestate. AD process …
simultaneous production of renewable energy and nutrient-rich digestate. AD process …
Forecasting gold price with the XGBoost algorithm and SHAP interaction values
SB Jabeur, S Mefteh-Wali, JL Viviani - Annals of Operations Research, 2024 - Springer
Financial institutions, investors, mining companies and related firms need an effective
accurate forecasting model to examine gold price fluctuations in order to make correct …
accurate forecasting model to examine gold price fluctuations in order to make correct …
The role of machine learning to boost the bioenergy and biofuels conversion
The development and application of bioenergy and biofuels conversion technology can play
a significant role for the production of renewable and sustainable energy sources in the …
a significant role for the production of renewable and sustainable energy sources in the …
Spatial heterogeneity modeling of water quality based on random forest regression and model interpretation
F Wang, Y Wang, K Zhang, M Hu, Q Weng… - Environmental …, 2021 - Elsevier
A systematic understanding of the spatial distribution of water quality is critical for successful
watershed management; however, the limited number of physical monitoring stations has …
watershed management; however, the limited number of physical monitoring stations has …
Machine learning and circular bioeconomy: Building new resource efficiency from diverse waste streams
Biorefinery systems are playing pivotal roles in the technological support of resource
efficiency for circular bioeconomy. Meanwhile, artificial intelligence presents great potential …
efficiency for circular bioeconomy. Meanwhile, artificial intelligence presents great potential …
Automated machine learning-based prediction of microplastics induced impacts on methane production in anaerobic digestion
RZ Xu, JS Cao, T Ye, SN Wang, JY Luo, BJ Ni, F Fang - Water research, 2022 - Elsevier
Microplastics as emerging pollutants have been heavily accumulated in the waste activated
sludge (WAS) during biological wastewater treatment, which showed significantly diverse …
sludge (WAS) during biological wastewater treatment, which showed significantly diverse …
Tree-based machine learning model for visualizing complex relationships between biochar properties and anaerobic digestion
The ideal conditions for anaerobic digestion experiments with biochar addition are
challenging to thoroughly study due to different experimental purposes. Therefore, three tree …
challenging to thoroughly study due to different experimental purposes. Therefore, three tree …
Review of explainable machine learning for anaerobic digestion
Anaerobic digestion (AD) is a promising technology for recovering value-added resources
from organic waste, thus achieving sustainable waste management. The performance of AD …
from organic waste, thus achieving sustainable waste management. The performance of AD …
Interpretable machine learning for predicting and evaluating hydrogen production via supercritical water gasification of biomass
S Zhao, J Li, C Chen, B Yan, J Tao, G Chen - Journal of Cleaner Production, 2021 - Elsevier
Supercritical water gasification (SCWG) of biomass for hydrogen production is a clean and
promising technology. However, due to many factors involved in SCWG process, including …
promising technology. However, due to many factors involved in SCWG process, including …