THE STUDY OF PREDICTING THE FLOW IN GAMASIAB RIVER BY THE INTELLIGENT SYSTEM OF THE ARTIFICIAL NEURAL NETWORKFarshid Salmani, Saeid Shabanlou and Hosein Fathian
The necessity to predict the flow in the rivers, in managing correctly the water resources for agricultural utilities, drinking water, industries, the input flow currents into the dam reservoirs, organizing the rivers, the flood alarming systems and etc have always made the river engineers to design some models being capable of predicting the flow with high capabilities and less error percentage. Therefore, the novel models of Artificial Neural Networks (ANNs) with their capabilities to make models of non-linear phenomenon not only are able to meet such needs without having the various parameters, and etc; but it has also gone beyond its other traditional counterparts, like Regersioni and the Time Sequence and it has also attracted the attention of the water engineers to itself. Thus aerological and hydrometric statistics (rainfall, discharge and transpiration) of the 23-water-year in a monthly time period on the Gamasiab River are used in this research paper and also MATLAB software, 7.8 in edition and the neural network is being used to make models to predict the flow currents. Some various patterns of data were considered the network input parameters. In addition, the two models of the neural systems, feed-forward back propagation and radial basic are used for modeling. The comparison deducted from the acquired results indicates the high capability of Rbf network in all of the patterns in predicting the flow and also the feed-forward back propagation in the patterns using the discharge input parameters and the upstream stations rainfall has had acceptable results.
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