Estimations of Sediments in Mahabad Dam Using Artificial Neural Networks and Comparing the Results w

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Estimations of Sediments in Mahabad Dam Using Artificial Neural Networks and Comparing the Results with Hydrometer Approach

Original Article, D37
Khezri H, Merufinia E.
J. Civil Eng. Urban. 4(3): 245-250. 2014

ABSTRACT: A deposition phenomenon is considered as one of the hydrometer processes which have ability to influence the most of the hydraulic structures and facility constructions. The exact assessment of the deposition of the rivers plays an important  role not only in the management of the water sources, but also it is deemed that this factor also may have an influence  on the designing, fabricating and planning phase of the utilization of Hydraulic Structures. In this survey, Neural Networks along with appropriate structure and self-training system is used as one of the methods of the estimating the amount of the sediments related to the Mahabad barrier, also the results of this survey are compared with the result of the hydrometer method. To this end, the discharge statistics of the water and sediments in two Cawter hydrometer station and Baitas village within the basin of Mahabad Dam catchment is investigated separately and at the end the estimation of the sediment load is compared and surveyed respectively by using neural networks in the Nero solution software via the multi-layer model of the Perceptron and the prevalent hydrometer approach. The results point out that the multi-layer networks in prognosticating a measure of the sediments is superior to hydrometer method.
Keywords: Artificial Neural Network, Hydrometer Method, Nero solution, Sediments.

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