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Review of explainable machine learning for anaerobic digestion

文献类型：期刊论文

作者Gupta, Rohit1,8,9; Zhang, Le2; Hou, Jiayi3; Zhang, Zhikai4,5; Liu, Hongtao3; You, Siming8; Ok, Yong Sik6,7; Li, Wangliang4
刊名BIORESOURCE TECHNOLOGY
出版日期2023-02-01
卷号369页码:10
ISSN号0960-8524
关键词Data -driven modelling Sustainable waste management Renewable energy Bioenergy Artificial intelligence
DOI10.1016/j.biortech.2022.128468
通讯作者Li, Wangliang(wlli@ipe.ac.cn)
英文摘要Anaerobic digestion (AD) is a promising technology for recovering value-added resources from organic waste, thus achieving sustainable waste management. The performance of AD is dictated by a variety of factors including system design and operating conditions. This necessitates developing suitable modelling and optimi-zation tools to quantify its off-design performance, where the application of machine learning (ML) and soft computing approaches have received increasing attention. Here, we succinctly reviewed the latest progress in black-box ML approaches for AD modelling with a thrust on global and local model interpretability metrics (e.g., Shapley values, partial dependence analysis, permutation feature importance). Categorical applications of the ML and soft computing approaches such as what-if scenario analysis, fault detection in AD systems, long-term operation prediction, and integration of ML with life cycle assessment are discussed. Finally, the research gaps and scopes for future work are summarized.
WOS关键词BIOGAS PRODUCTION ; VFA CONCENTRATION ; FAULT-DETECTION ; WASTE ; OPTIMIZATION ; MODEL
资助项目National Natural Science Foundation of China[21878313] ; UK Engineering and Physical Sciences Research Council (EPSRC)[EP/V030515/1] ; Supergen Bioenergy Hub Rapid Response Funding[RR 2022_10] ; Royal Society Research Grant[RGS\R1 \211358] ; Royal Society Newton International Fellowship[NIF\R1\211013] ; Cooperative Research Program for Agriculture Science and Technology Development from Rural Development Administration, the Republic of Korea[PJ01475801] ; Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education[NRF-2021R1A6A1A10045235]
WOS研究方向Agriculture ; Biotechnology & Applied Microbiology ; Energy & Fuels
语种英语
出版者ELSEVIER SCI LTD
WOS记录号WOS:000912514700001
资助机构National Natural Science Foundation of China ; UK Engineering and Physical Sciences Research Council (EPSRC) ; Supergen Bioenergy Hub Rapid Response Funding ; Royal Society Research Grant ; Royal Society Newton International Fellowship ; Cooperative Research Program for Agriculture Science and Technology Development from Rural Development Administration, the Republic of Korea ; Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education
源URL[http://ir.igsnrr.ac.cn/handle/311030/189819]  
专题中国科学院地理科学与资源研究所
通讯作者Li, Wangliang
作者单位1.UCL, Wellcome EPSRC Ctr Intervent & Surg Sci, London W1W, England
2.Shanghai Jiao Tong Univ, Sch Agr & Biol, Dept Resources & Environm, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
4.Chinese Acad Sci, Inst Proc Engn, CAS Key Lab Green Proc & Engn, Beijing 100190, Peoples R China
5.Hebei GEO Univ, Sch Water Resources & Environm, Shijiazhuang 050031, Hebei, Peoples R China
6.Korea Univ, Korea Biochar Res Ctr, APRU Sustainable Waste Management Program, Seoul 02841, South Korea
7.Korea Univ, Korea Biochar Res Ctr, Div Environm Sci & Ecol Engn, Seoul 02841, South Korea
8.Univ Glasgow, James Watt Sch Engn, Glasgow City G12 8QQ, Scotland
9.UCL, Nanoengn Syst Lab, UCL Mech Engn, London WC1E 7JE, England
推荐引用方式
GB/T 7714		 Gupta, Rohit,Zhang, Le,Hou, Jiayi,et al. Review of explainable machine learning for anaerobic digestion[J]. BIORESOURCE TECHNOLOGY,2023,369:10.
APA Gupta, Rohit.,Zhang, Le.,Hou, Jiayi.,Zhang, Zhikai.,Liu, Hongtao.,...&Li, Wangliang.(2023).Review of explainable machine learning for anaerobic digestion.BIORESOURCE TECHNOLOGY,369,10.
MLA Gupta, Rohit,et al."Review of explainable machine learning for anaerobic digestion".BIORESOURCE TECHNOLOGY 369(2023):10.

入库方式： OAI收割

来源：地理科学与资源研究所

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