Penelusuran Banjir (Flood Routing) Terhadap Muka Air Sungai Dengan Metode Jaringan Saraf Tiruan (Studi Kasus DAS Kampar Dan DAS Siak) - Rico Ardiansyah Amri; Manyuk Fauzi; Siswanto Siswanto (Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains, 2014)
River water level data forecasting Qn to Qn+1 by using Artificial Neural Network model approach Backpropagation algorithm produces good value if the value of the correlation between upstream and downstream AWLR good enough, it can be seen from the process of training, testing and validation of the neural network that generates the value correlation learning high enough. Where in the wake of the artificial neural network model Backporagation algorithms using MATLAB programs, such as for this parameter is Epoch = 2000, Ir = 0.1, mc = 0.9. Data Variation 70 (training) and 30 (Tests), it is proven in testing the artificial neural network model is applied to predict water levels in 2012. So this data can be a flood early warning system in the downstream areas of the river.Keyword : neural network, the back propagation algorithm, face high water forecasting