ANN And GA Methods To Identify The Non-point Contamination Flux To Groundwater
Author(s)
K.Hiramatsu, E.Ichion, T.Kawachi, J.Takeuchi
Abstract
ANN and GA methods to identify the non-point
contamination flux to groundwater
K. Hiramatsu*, E. Ichion^, T. Kawachi*, & J. Takeuchi*
'Division of Environmental Science and Technology, Kyoto University,
Japan
* Department of Agricultural Engineering, Ishikawa Agricultural College,
Japan
Abstract
Contamination of groundwater due to non-point source, e.g., excessive fer-
tilizer use in farming, is becoming a serious problem in many parts of the
world. Quality of groundwater is often monitored at wells for its appro-
priate management. However, methodologies to identify the incoming flux
values, inversely from the monitored data, are not completely established
yet and still developing. In this research, two types of the identification
methods, i.e., artificial neural network (ANN) and genetic algorithm (GA)
methods are presented. ANN and GA are similarly employed to identify
the incoming flux of contamination, combined with numerical solute trans-
port simulations. Their applicabil
Keywords
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