In recent years, artificial neural networks (ANNs) have been applied to estimate in many areas of hydrology and hydraulic engineering. In this thesis, multilayered feedforward backpropagation algorithm was used to establish for the prediction of unit discharge q (m3/s/m) in a rectangular free overfall. Researchers&rsquo / experimental data were used to train and validate the network with high reliability. First, an appropriate ANN model has been established by considering determination of hidden layer and node numbers related to training function and training epoch number. Then by applying sensitivity analysis, parameters involved in and their effectiveness relatively has been determined in the phenomenon. In the scope of the thesis, there are two case studies. In the first case study, ANN models reliability has been investigated according to the training data clustered and the results are given by comparing to regression analysis. In the second case, ANN models&rsquo / ability in establishing relations with different data clusters is investigated and effectiveness of ANN is scrutinized.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12606706/index.pdf |
| Date | 01 October 2005 |
| Creators | Ozturk, Hayrullah Ugras |
| Contributors | Ger, Ahmet Metin |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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