Predicting and Evaluating Different Pretreatment Methods on Methane Production from Sludge Anaerobic Digestion via Automated Machine Learning with Ensembled Semisupervised Learning

Accurate prediction of methane production in anaerobic digestion with various pretreatment strategies is of the utmost importance for efficient sludge treatment and resource recovery. Traditional machine learning (ML) algorithms have shown limited prediction accuracy due to challenges in optimizing...

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Bibliographic Details
Main Author:	Xiaoshi Cheng (14119418) (author)
Other Authors:	Runze Xu (9749033) (author), Yang Wu (66682) (author), Baiyang Tang (17253433) (author), Yuting Luo (1465735) (author), Wenxuan Huang (4434001) (author), Feng Wang (44414) (author), Shiyu Fang (12239115) (author), Qian Feng (302178) (author), Yu Cheng (136592) (author), Song Cheng (4672219) (author), Jingyang Luo (2828585) (author)
Published:	2023
Subjects:	Biochemistry Pharmacology Computational Biology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified volatile fatty acids traditional machine learning optimizing complex parameters offering valuable guidance novel integrated system mean squared error insights shed light ensemble semisupervised learning chemical oxygen demand various pretreatment strategies efficient sludge treatment limited variable inputs correlation analysis unveiled effective sludge pretreatment xgb ), etc conventional ml models 2 </ sup anaerobic digestion systems predicting methane production automl model outperformed methane production sludge digestion anaerobic digestion pretreatment type r </ hidden variable explainable analysis >< sup digestion substrates work proposed utmost importance results demonstrated resource recovery principal component prediction accuracy operating time microbial communities metabolic functions key variables functional microbial direct correlations different variables different pretreatments dependence relationships
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Predicting and Evaluating Different Pretreatment Methods on Methane Production from Sludge Anaerobic Digestion via Automated Machine Learning with Ensembled Semisupervised Learning

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