Preliminary communication

Suspended sediment modelling by SVM and wavelet

Maedeh Sadeghpour Haji ; Islamsko sveučilište Azad, Zavod za ekološko inženjerstvo, okoliš i energetiku
Seyed A. Mirbagheri ; Tehnološko sveučilište K.N. Toosi, Zavod za građevinarstvo i ekološko inženjerstvo
Amir H. Javid ; Islamsko sveučilište Azad, Odjel za znanost i straživanja
Mostafa Khezri ; Islamsko sveučilište Azad, Fakultet za okoliš i energetiku
Ghasem D. Najafpour ; Tehnološko sveučilište Babol Noshirvani, Istraživački centar za biotehnologiju

Abstract

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.

Keywords

Discrete wavelet analysis; Cumulative SS; Daily stream flow; High suspended sediment; Support vector machine

Hrčak ID:

119898

URI

https://hrcak.srce.hr/119898

Publication date:

10.4.2014.

Article data in other languages: croatian

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