The artificial neural network (ANN) approach, which is a non-linear ...

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20 Οκτ 2013 (πριν από 4 χρόνια και 7 μήνες)

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Artificial Neural Networks in Water Resources

H.Kerem Cigizoglu

Associate Prof., Hydraulics Division, Civil Engineering Faculty,
Istanbul Technical University,
stanbul, Turkey

Key words :

artificial neural network, hydrologic time series, forecasting,
feed forward back
propagation, radial basis functions, generalized regression neural network


The artificial neural network (ANN) approach, which is a non
linear black box model,
would seem to be a useful alternative for modeling the
water resource
s time

series. The ANN
applications in water resources are in river flow prediction, in the rainfall
runoff relationship,
in rainfall estimation

in various groundwater problems

and in suspended sediment modelling

In the majority of these studies, the fe
forward error back
propagation method (FFBP) was
employed to train the neural networks. The performance of the FFBP was found to be
superior to conventional statistical and stochastic methods in continuous flow series
forecasting. However, the FFBP algo
rithm has some drawbacks such as the local minima
In this study relatively new ANN methods such as
the radial basis function

generalized regression neural network are employed in the modeling of hydrologic time series
together with FFBP method
. The results are compared with those of the conventional
statistical methods.