APLIKASI ALGORITMA BACKPROPAGATION FEEDFORWARD NEURAL NETWORKS UNTUK PREDIKSI ALIRAN SUNGAI (STUDI KASUS DAS GUMBASA, PALU SULTENG) - Rais Rais (Program Studi Matematika, Universitas Tadulako, 2009)
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.