Using automated machine learning techniques to explore key factors in anaerobic digestion: At the environmental factor, microorganisms and system levels
Author:
Publisher
Elsevier BV
Subject
Industrial and Manufacturing Engineering,General Chemical Engineering,Environmental Chemistry,General Chemistry
Reference45 articles.
1. A review of process parameters influence in solid-state anaerobic digestion: Focus on performance stability thresholds;Ajayi-Banji;Renew. Sustain. Energy Rev.,2022
2. Application of machine learning in anaerobic digestion: Perspectives and challenges;Andrade Cruz;Bioresour. Technol.,2022
3. Anaerobic Thermophilic Digestion of Maotai-Flavored Distiller’s Grains: Process Performance and Microbial Community Dynamics;Ao;Energy Fuel,2019
4. Automatic gap-filling of daily streamflow time series in data-scarce regions using a machine learning algorithm;Arriagada;J. Hydrol.,2021
5. Mathematical modelling of anaerobic digestion processes: applications and future needs;Batstone;Rev. Environ. Sci. Bio/Technol.,2015
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