Application of machine learning in anaerobic digestion: Perspectives and challenges

[Display omitted] •Machine learning assisted decision-making is an emerging approach.•Various machine learning models have been applied for prediction and optimization.•Anaerobic digestion instability can be reduced using machine learning algorithms.•Further research on practical application and alg...

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Vydané v:	Bioresource technology Ročník 345; s. 126433
Hlavní autori:	Andrade Cruz, Ianny, Chuenchart, Wachiranon, Long, Fei, Surendra, K.C., Renata Santos Andrade, Larissa, Bilal, Muhammad, Liu, Hong, Tavares Figueiredo, Renan, Khanal, Samir Kumar, Fernando Romanholo Ferreira, Luiz
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Elsevier Ltd 01.02.2022
Predmet:	Anaerobic digestion Anaerobiosis Biofuels Bioreactors gas production (biological) Machine Learning Methane Modeling prediction Process instability Process optimization renewable energy sources TAN FVW DL CHP AHR HRT ZVI FFN DT MLP TVS PNN RNN OLR RBF ANFIS ML RFR AD VFAs PSO RSM PCA GIS BPA AT FCMC GEP RF VS OFMSW ANN GRN ENN FL KNN NNET SVM MNN ORP FS Modeling BP Anaerobic digestion Process instability CBP SC LS-SVM SRT C:N XGBoost COD GMLET GA WFM COM Process optimization AcoD GP CM RMSE MSS ACO LMM CSTR Machine learning FOS/TAC FF-BPNN MFs UASB ICV TS
ISSN:	0960-8524, 1873-2976, 1873-2976
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