Comparison of machine learning methods for predicting the methane production from anaerobic digestion of lignocellulosic biomass
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DOI: 10.1016/j.energy.2022.125883
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- Wu, Benteng & Lin, Richen & Bose, Archishman & Huerta, Jorge Diaz & Kang, Xihui & Deng, Chen & Murphy, Jerry D., 2023. "Economic and environmental viability of biofuel production from organic wastes: A pathway towards competitive carbon neutrality," Energy, Elsevier, vol. 285(C).
- He, Xiaoman & Deng, Chen & Li, Pengfei & Yu, Wenbing & Chen, Huichao & Lin, Richen & Shen, Dekui & Baroutian, Saeid, 2024. "The impact of salinity on biomethane production and microbial community in the anaerobic digestion of food waste components," Energy, Elsevier, vol. 294(C).
- Liu, Changyu & Sun, Yongxiang & Bian, Ji & Hu, Wanyu & Zhang, Chengjun & Wu, Yangyang & Li, Pengfei & Li, Dong, 2023. "Mechanism of solar photo-thermal transformation for baffled liquid on energy and mass transfer efficiency in direct absorption anaerobic reactor," Energy, Elsevier, vol. 278(PA).
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Keywords
Machine learning; Lignocellulosic biomass; Anaerobic digestion; Specific methane yield; Prediction;All these keywords.
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