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Comparison of wavelet based hybrid models for daily evapotranspiration estimation using meteorological data

Partal, Turgay

Abstract This paper investigates the comparative performance of wavelet based radial basis networks and multi linear regression in daily reference evapotranspiration estimation. The meteorological data (air temperature, solar radiation, wind speed, relative humidity) from two stations in the United States was evaluated for estimating models. The wavelet based radial basis network combines wavelet transformation and radial basis neural network, while the wavelet based regression model combines wavelet transformation and multi linear regression. The results show that the wavelet transformation has significantly positive effects on modeling performance. The wavelet based radial basis network provided the best performance evaluation criteria.

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Comparison of wavelet based hybrid models for daily evapotranspiration estimation using meteorological data

Partal, Turgay

Abstract This paper investigates the comparative performance of wavelet based radial basis networks and multi linear regression in daily reference evapotranspiration estimation. The meteorological data (air temperature, solar radiation, wind speed, relative humidity) from two stations in the United States was evaluated for estimating models. The wavelet based radial basis network combines wavelet transformation and radial basis neural network, while the wavelet based regression model combines wavelet transformation and multi linear regression. The results show that the wavelet transformation has significantly positive effects on modeling performance. The wavelet based radial basis network provided the best performance evaluation criteria.

Comparison of wavelet based hybrid models for daily evapotranspiration estimation using meteorological data

Partal, Turgay

Abstract This paper investigates the comparative performance of wavelet based radial basis networks and multi linear regression in daily reference evapotranspiration estimation. The meteorological data (air temperature, solar radiation, wind speed, relative humidity) from two stations in the United States was evaluated for estimating models. The wavelet based radial basis network combines wavelet transformation and radial basis neural network, while the wavelet based regression model combines wavelet transformation and multi linear regression. The results show that the wavelet transformation has significantly positive effects on modeling performance. The wavelet based radial basis network provided the best performance evaluation criteria.

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Title:

Comparison of wavelet based hybrid models for daily evapotranspiration estimation using meteorological data

Contributors:

Partal, Turgay (author)

Published in:

KSCE Journal of Civil Engineering ; 20 ; 2050-2058

Publication date:

2015-10-16

Size:

9 pages

ISSN:

1976-3808 , 1226-7988

DOI:

https://doi.org/10.1007/s12205-015-0556-0

Type of media:

Article (Journal)

Type of material:

Electronic Resource

Language:

English

Keywords:

wavelet transformation , radial basis neural network , feed forward neural network , multi linear regression , evapotranspiration , estimating Engineering , Civil Engineering , Industrial Pollution Prevention , Geotechnical Engineering & Applied Earth Sciences

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