title: Estimation of biogas and methane yields in an UASB treating potato starch processing wastewater with backpropagation artificial neural network.
abstract: Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW). Anaerobic process parameters were optimized to identify their importance on methanation. pH, total chemical oxygen demand, ammonium, alkalinity, total Kjeldahl nitrogen, total phosphorus, volatile fatty acids and hydraulic retention time selected based on principal component analysis were used as input variables, whiles biogas and methane yield were employed as target variables. Quasi-Newton method and conjugate gradient backpropagation algorithms were best among eleven training algorithms. Coefficient of determination (R2) of the BP-ANN reached 98.72% and 97.93% whiles MnLR model attained 93.9% and 91.08% for biogas and methane yield, respectively. Compared with the MnLR model, BP-ANN model demonstrated significant performance, suggesting possible control of the anaerobic digestion process with the BP-ANN model.
authors.affiliation: State Key Laboratory of Urban Water Resource and Environment, School of Municipal and Environmental Engineering, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, PR China.
authors.forename: Philip
authors.initials: P
authors.lastname: Antwi
authors.affiliation: State Key Laboratory of Urban Water Resource and Environment, School of Municipal and Environmental Engineering, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, PR China. Electronic address: ljz667@163.com.
authors.forename: Jianzheng
authors.initials: J
authors.lastname: Li
authors.affiliation: School of Management, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin 150001, PR China.
authors.forename: Portia Opoku
authors.initials: PO
authors.lastname: Boadi
authors.affiliation: State Key Laboratory of Urban Water Resource and Environment, School of Municipal and Environmental Engineering, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, PR China.
authors.forename: Jia
authors.initials: J
authors.lastname: Meng
authors.affiliation: State Key Laboratory of Urban Water Resource and Environment, School of Municipal and Environmental Engineering, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, PR China.
authors.forename: En
authors.initials: E
authors.lastname: Shi
authors.affiliation: State Key Laboratory of Urban Water Resource and Environment, School of Municipal and Environmental Engineering, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, PR China.
authors.forename: Kaiwen
authors.initials: K
authors.lastname: Deng
authors.affiliation: School of Energy, Geoscience, Infrastructure and Society, Institute for Social Policy, Housing, Environment and Real Estate, Heriot-Watt University, UK.
authors.forename: Francis Kwesi
authors.initials: FK
authors.lastname: Bondinuba
mesh_terms: D000465:Algorithms; D000693:Anaerobiosis; D056804:Biofuels / Q000032:analysis*; D057919:Biological Oxygen Demand Analysis; D019149:Bioreactors; D008697:Methane / Q000096:biosynthesis*; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D012044:Regression Analysis; D012722:Sewage / Q000382:microbiology; D011198:Solanum tuberosum / Q000737:chemistry*; D013213:Starch / Q000737:chemistry*; D062065:Wastewater / Q000032:analysis*
chemical_list: D056804:Biofuels; D008697:Methane; D012722:Sewage; D013213:Starch; D062065:Wastewater
keywords: Artificial neural networks; Methane yield; Optimized; Potato starch processing wastewater; Upflow anaerobic sludge blanket