Suspended sediment modelling by SVM and wavelet
Present-day advances in artificial intelligence, as a forecaster for hydrological events, have led to numerous changes in forecasting. The wavelet support vector machine (WSWM) model is achieved by conjunction of the wavelet analysis and the support vector machine (SVM). The suspended sediment (SS)...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Croatian Association of Civil Engineers
2014-04-01
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| Series: | Građevinar |
| Online Access: | https://doi.org/10.14256/JCE.981.2013 |
| _version_ | 1828517877797355520 |
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| author | Maedeh Sadeghpour Haji Seyed A. Mirbagheri Amir H. Javid Mostafa Khezri Ghasem D. Najafpour |
| author_facet | Maedeh Sadeghpour Haji Seyed A. Mirbagheri Amir H. Javid Mostafa Khezri Ghasem D. Najafpour |
| author_sort | Maedeh Sadeghpour Haji |
| collection | DOAJ |
| description | Present-day advances in artificial intelligence, as a forecaster for hydrological events, have led to numerous changes in forecasting. The wavelet support vector machine (WSWM) model is achieved by conjunction of the wavelet analysis and the support vector machine (SVM). The suspended sediment (SS) and daily stream flow (Q) data from the Iowa River in the USA were used for training and testing. The WSVM could logically be used for approximation of the suspended sediment load. |
| first_indexed | 2024-12-11T18:47:30Z |
| format | Article |
| id | doaj.art-27ce8966c83b4d6a99bd206eca15f65b |
| institution | Directory Open Access Journal |
| issn | 0350-2465 1333-9095 |
| language | English |
| last_indexed | 2024-12-11T18:47:30Z |
| publishDate | 2014-04-01 |
| publisher | Croatian Association of Civil Engineers |
| record_format | Article |
| series | Građevinar |
| spelling | doaj.art-27ce8966c83b4d6a99bd206eca15f65b2022-12-22T00:54:25ZengCroatian Association of Civil EngineersGrađevinar0350-24651333-90952014-04-016603.21122310.14256/JCE.981.2013119898Suspended sediment modelling by SVM and waveletMaedeh Sadeghpour Haji0Seyed A. Mirbagheri1Amir H. Javid2Mostafa Khezri3Ghasem D. Najafpour4Islamsko sveučilište Azad, Zavod za ekološko inženjerstvo, okoliš i energetikuTehnološko sveučilište K.N. Toosi, Zavod za građevinarstvo i ekološko inženjerstvoIslamsko sveučilište Azad, Odjel za znanost i straživanjaIslamsko sveučilište Azad, Fakultet za okoliš i energetikuTehnološko sveučilište Babol Noshirvani, Istraživački centar za biotehnologijuPresent-day advances in artificial intelligence, as a forecaster for hydrological events, have led to numerous changes in forecasting. The wavelet support vector machine (WSWM) model is achieved by conjunction of the wavelet analysis and the support vector machine (SVM). The suspended sediment (SS) and daily stream flow (Q) data from the Iowa River in the USA were used for training and testing. The WSVM could logically be used for approximation of the suspended sediment load.https://doi.org/10.14256/JCE.981.2013 |
| spellingShingle | Maedeh Sadeghpour Haji Seyed A. Mirbagheri Amir H. Javid Mostafa Khezri Ghasem D. Najafpour Suspended sediment modelling by SVM and wavelet Građevinar |
| title | Suspended sediment modelling by SVM and wavelet |
| title_full | Suspended sediment modelling by SVM and wavelet |
| title_fullStr | Suspended sediment modelling by SVM and wavelet |
| title_full_unstemmed | Suspended sediment modelling by SVM and wavelet |
| title_short | Suspended sediment modelling by SVM and wavelet |
| title_sort | suspended sediment modelling by svm and wavelet |
| url | https://doi.org/10.14256/JCE.981.2013 |
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