Pournouri, Z. (2014) Simulaiting the flow discharge of Marbareh basin by artificial neural network and fuzzy-neural. Masters thesis, University of Zabol.
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Abstract
River flow simulation is as the first and most important step for flood control in water resources management. In this study, the daily flow Marboreh River in the Lorestan province, using artificial neural networks and examined with Adaptive Neural-Fuzzy Inference System. Based on different combinations of rainfall and temperature parameters of the desired time period and river flows in the periods before, during statistical period (1377-1391) as an input and an output parameter in the river flow in the desired period of time scale of evaluated daily. Criteria of correlation coefficient, root mean square and Nash-Sutcliff to evaluate and compare the performance of methods was used. The results showed that the model combines the input stream flow in prehistoric period and temperature and precipitation in desired time period could using evaluated two artificial intelligence models, provide acceptable results in simulating the river flow. Comparison of both methods showed the accuracy, ANFIS model with a correlation coefficient (0.970), root mean square error (0.001m3 / s) and Nash Sutcliff (0.928) was priority in the verification stage. Overall, the results indicated that the estimated values of the minimum and intermediate ANFIS high capacity and good correlation with the observed value.
| Item Type: | Thesis (Masters) |
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| Uncontrolled Keywords: | River flow, Artifical neural network, Anfis, Artificial intelligenc |
| Subjects: | S Agriculture > S Agriculture (General) |
| Depositing User: | Mrs najmeh khajeh |
| Date Deposited: | 02 Oct 2022 05:34 |
| Last Modified: | 02 Oct 2022 05:34 |
| URI: | http://eprints.uoz.ac.ir/id/eprint/3105 |
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