Evaluvating the Performance of Wavelet Neural Network Models in Estimation of Daily Discharge
River flow prediction is one of the most important key issues in the management and planning of water resources, in particular the adoption of proper decisions in the event of floods and the occurrence of droughts. In order to predict the flow rate of rivers, various approaches have been introduced...
| Main Authors: | , |
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| Format: | Article |
| Language: | fas |
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Shahid Chamran University of Ahvaz
2019-09-01
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| Series: | علوم و مهندسی آبیاری |
| Subjects: | |
| Online Access: | http://jise.scu.ac.ir/article_14818_0cc89d3259f60ed35bfc09e9822a1f00.pdf |
| _version_ | 1818309547232591872 |
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| author | Hamidreza Babaali Reza Dehghani |
| author_facet | Hamidreza Babaali Reza Dehghani |
| author_sort | Hamidreza Babaali |
| collection | DOAJ |
| description | River flow prediction is one of the most important key issues in the management and planning of water resources, in particular the adoption of proper decisions in the event of floods and the occurrence of droughts. In order to predict the flow rate of rivers, various approaches have been introduced in hydrology, in which intelligent models are the most important ones. The application of artificial neural networks (ANNs) to various aspects of hydrological modeling has undergone much investigation in recent years. This interest has been motivated by the complex nature of hydrological systems and the ability of ANNs to model non-linear relationships. ANNs are essentially semi-parametric regression estimators and well suited for hydrological modeling, as they can approximate virtually any (measurable) function up to an arbitrary degree of accuracy (Hornik et al., 1989). A significant advantage of the ANN approach in system modeling is that one need not have a well-defined process for algorithmically converting an input to an output. |
| first_indexed | 2024-12-13T07:31:54Z |
| format | Article |
| id | doaj.art-c3733aa0cb394812b2a55324028087c8 |
| institution | Directory Open Access Journal |
| issn | 2588-5952 2588-5960 |
| language | fas |
| last_indexed | 2024-12-13T07:31:54Z |
| publishDate | 2019-09-01 |
| publisher | Shahid Chamran University of Ahvaz |
| record_format | Article |
| series | علوم و مهندسی آبیاری |
| spelling | doaj.art-c3733aa0cb394812b2a55324028087c82022-12-21T23:55:11ZfasShahid Chamran University of Ahvazعلوم و مهندسی آبیاری2588-59522588-59602019-09-0142310511610.22055/jise.2017.22047.158014818Evaluvating the Performance of Wavelet Neural Network Models in Estimation of Daily DischargeHamidreza Babaali0Reza Dehghani1Assistant Professor of Civil Engineering, Islamic Azad University, Khorramabad.Ph.D. Student of Water Structure, Faculty of Agric., University of Lorestan, Khorramabad, Iran.(River flow prediction is one of the most important key issues in the management and planning of water resources, in particular the adoption of proper decisions in the event of floods and the occurrence of droughts. In order to predict the flow rate of rivers, various approaches have been introduced in hydrology, in which intelligent models are the most important ones. The application of artificial neural networks (ANNs) to various aspects of hydrological modeling has undergone much investigation in recent years. This interest has been motivated by the complex nature of hydrological systems and the ability of ANNs to model non-linear relationships. ANNs are essentially semi-parametric regression estimators and well suited for hydrological modeling, as they can approximate virtually any (measurable) function up to an arbitrary degree of accuracy (Hornik et al., 1989). A significant advantage of the ANN approach in system modeling is that one need not have a well-defined process for algorithmically converting an input to an output.http://jise.scu.ac.ir/article_14818_0cc89d3259f60ed35bfc09e9822a1f00.pdfestimationfloodartificial neural networknourabad |
| spellingShingle | Hamidreza Babaali Reza Dehghani Evaluvating the Performance of Wavelet Neural Network Models in Estimation of Daily Discharge علوم و مهندسی آبیاری estimation flood artificial neural network nourabad |
| title | Evaluvating the Performance of Wavelet Neural Network Models in Estimation of Daily Discharge |
| title_full | Evaluvating the Performance of Wavelet Neural Network Models in Estimation of Daily Discharge |
| title_fullStr | Evaluvating the Performance of Wavelet Neural Network Models in Estimation of Daily Discharge |
| title_full_unstemmed | Evaluvating the Performance of Wavelet Neural Network Models in Estimation of Daily Discharge |
| title_short | Evaluvating the Performance of Wavelet Neural Network Models in Estimation of Daily Discharge |
| title_sort | evaluvating the performance of wavelet neural network models in estimation of daily discharge |
| topic | estimation flood artificial neural network nourabad |
| url | http://jise.scu.ac.ir/article_14818_0cc89d3259f60ed35bfc09e9822a1f00.pdf |
| work_keys_str_mv | AT hamidrezababaali evaluvatingtheperformanceofwaveletneuralnetworkmodelsinestimationofdailydischarge AT rezadehghani evaluvatingtheperformanceofwaveletneuralnetworkmodelsinestimationofdailydischarge |