title: A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks.
abstract: A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2(0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.
authors.affiliation: Department of Water Resources and Environment, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, PR China.
authors.forename: Mingzhi
authors.initials: M
authors.lastname: Huang
authors.affiliation: School of Environmental Science and Engineering, Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-Sen University, Guangzhou 510275, PR China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhang
authors.affiliation: School of Environmental Science and Engineering, Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-Sen University, Guangzhou 510275, PR China.
authors.forename: Jujun
authors.initials: J
authors.lastname: Ruan
authors.affiliation: Department of Water Resources and Environment, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, PR China.
authors.forename: Xiaohong
authors.initials: X
authors.lastname: Chen
mesh_terms: D000332:Aerobiosis; D000465:Algorithms; D000693:Anaerobiosis; D001673:Biodegradation, Environmental; D017143:Fuzzy Logic; D007700:Kinetics; D016571:Neural Networks, Computer; D010795:Phthalic Acids / Q000378:metabolism*
chemical_list: D010795:Phthalic Acids; C024629:dimethyl phthalate