Modeling the impact of some independent parameters on the syngas characteristics during plasma gasification of municipal solid waste using artificial neural network and stepwise linear regression methods
【作者单位】[a]School of Environmental Science and Engineering, Tianjin University/Tianjin Key Lab of Biomass/Wastes Utilization, Tianjin, 300072, ChinaSchool of Environmental Science and Engineering, Tianjin University/Tianjin Key Lab of Biomass/Wastes Utilization, Tianjin 300072, China[b]School of Science, Tibet University, Lhasa, 850012, Tibet, ChinaSchool of Science, Tibet University, Lhasa 850012, Tibet, China[c]Qingdao Institute for Marine Technology of Tianjin University, Qingdao, 266235, ChinaQingdao Institute for Marine Technology of Tianjin University, Qingdao 266235, China[d]Shanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, ChinaShanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China[e]School of Environmental Science and Engineering, Renmin University of China, Beijing, 100872, ChinaSchool of Environmental Science and Engineering, Renmin University of China, Beijing 100872, China[f]United Nations Environment Programme (UNEP), Nairobi, P.O. Box 30552, KenyaUnited Nations Environment Programme (UNEP) , Nairobi, P.O. Box 30552, Kenya
【年份】2022
【卷号】Vol.157 No.0
【ISSN】1364-0321
【关键词】Thermal plasma Gasification Municipal solid waste Stepwise linear regression Artificial neural network Syngas characteristics
【摘要】 Thermal plasma gasification is considered as an attractive technology to produce high quality syngas from municipal solid waste . It is imperative to study the effect of operating parameters on syngas quality and find a practical way to predict synga...
