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Forecasting Daily Stream Flows of Vaniar River Using Genetic Programming and Neural Networks Approaches Original Article, C31 Roushangar K, Vojoudi Mehrabani F, Alami M.T Journal. Civil Eng. Urban. 3(4):197-200. 2013 ABSTRACT:This study compares three different artificial intelligence approaches, namely, gene expression programming (GEP), and artificial neural networks (ANN), in daily as well as monthly streamflow forecasting. Daily streamflow data from Vaniar River in the Northwestern Iran were used. Coefficient of determination, root mean square error and scatter index were used to compare simulation results. The study demonstrates that the optimal results were obtained from the triple-input models including streamflows of current and two previous days and that the GEP model performed better than the ANN model in daily streamflow forecasting. Keywords: Gene Expression Programming, Neural Networks, Forecasting منبع: [Hidden Content] دانلود: [Hidden Content].,31-197-200.pdf J. Civil Eng. Urban.,31-197-200.pdf