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《Environmental Science & Technology》 2012-01
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A Neural Network Based Model for Simulating the Transport of Heavy Metals in Reservoir

ZHANG Ming1,SHEN Yong-ming1,ZHEN Hong2,FENG Yu2,SHANG Hong-zhi2(1.State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technology,Dalian 116023,China; 2.Liaoning Academy of Environmental Science,Shenyang 110031,China)  
The transport of heavy metals in aquatic environment is complicated and can be affected by many factors.It is a focal point to simulate the heavy metal transport in water body quickly and precisely.Artificial neural networks(NN),which computes rapidly and can be implemented to any desired degree of accuracy in fitting any nonlinear function,have been successfully applied in modeling most of water quality indices,but not so when turn to heavy metals.The paper described an application of artificial neural network for modeling the transport of heavy metals such as Cd,Cu,Hg and Zn in Dahuofang Reservoir.According to the mechanism of heavy metal transport and using the idea of settling boundary value problems in mathematical model for reference,the input and output factors of the NN were determined.The heavy metal concentrations that can not be detected or are below the detection limit of the given detection method were computed as 0.The outputs of NN models for all four heavy metals were compared with the measured data.The maximum relative error(MaxRE) of Cd and Cu for each of their test datasets is 17.5% and 17.9% respectively.The coefficient of determination(R2) of Hg and Zn for their test datasets is 0.741 and 0.762 respectively,and that of Cd and Cu is even higher than 0.96.The results of NN model of each heavy metal show that NN is able to simulate the transport of heavy metals in aquatic environment and can provide reliable results.NN models for simulating the transport of heavy metals in the Reservoir is instructive to water environment management in reservoir.
【Fund】: 国家水体污染控制与治理科技重大专项子课题(2009ZX07528-006-01);; 国家自然科学基金项目(51179025)
【CateGory Index】: X524
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