Predicting and Evaluating Different Pretreatment Methods on Methane Production from Sludge Anaerobic Digestion via Automated Machine Learning with Ensembled Semisupervised Learning-Reference-Cited by-同舟云学术

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

Published:2023-10-19 Issue: Volume: Page:
ISSN:2690-0645
Container-title:ACS ES&T Engineering
language:en
Short-container-title:ACS EST Eng.

Author:

Cheng Xiaoshi¹²,Xu Runze¹²^ORCID,Wu Yang³^ORCID,Tang Baiyang¹²,Luo Yuting¹²,Huang Wenxuan¹²,Wang Feng¹²,Fang Shiyu¹²,Feng Qian¹²,Cheng Yu¹²,Cheng Song¹²^ORCID,Luo Jingyang¹²^ORCID

Affiliation:

1. Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, 1 Xikang Road, Nanjing 210098, P. R. China

2. College of Environment, Hohai University, 1 Xikang Road, Nanjing 210098, P. R. China

3. State Key Laboratory of Pollution Control and Resource Reuse, School of Environmental Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, P. R. China

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Priority Academic Program Development of Jiangsu Higher Education Institutions

Publisher

American Chemical Society (ACS)

Subject

Chemical Health and Safety,Process Chemistry and Technology,Environmental Chemistry,Chemical Engineering (miscellaneous)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsestengg.3c00368

Reference64 articles.

1. Antimicrobial PCMX facilitates the volatile fatty acids production during sludge anaerobic fermentation: Insights of the interactive principles, microbial metabolic profiles and adaptation mechanisms