Abstract: Hydrological models
are necessary in assessing water resources and valuable tool for water
resources management. This paper describes applications of feedforward neural
networks (FFNN) for Gumbasa watershed in Palu
Sulteng, Indonesia. Back-propagation was
used in the
learning rule of
FFNN. A series of daily rainfall,
evapotranspiration and discharge data for 2 years (2006-2007) from Gumbasa watershed
was used. The accuracy
is evaluated by
statistical performance index,
the shape of hydrographs and the
flood peaks. The results show that FFNN
is successful in predicting watershed discharge
in Cidanau watershed. These
hydrological models have
been developed in form
of application program Matlab 7.0.4 and applicable to use in other
watershed.
Keywords: Artificial Neural
Network, backpropagation, prediction, discharge
Penulis: Rais Rais
Kode Jurnal: jpmatematikadd090025
Artikel Terkait :
