| Autor: |
Eyyup Ensar Başakın, Ömer Ekmekcioğlu, Paul C. Stoy, Mehmet Özger |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
MethodsX, Vol 10, Iss , Pp 102163- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2215-0161 |
| DOI: |
10.1016/j.mex.2023.102163 |
| Popis: |
In this study, stochastic gradient boosting (SGB), a commonly-adopted soft computing method, was used to estimate reference evapotranspiration (ETo) for the Adiyaman region of southeastern Türkiye. The FAO-56-Penman-Monteith method was used to calculate ETo, which we then estimated using SGB with maximum temperature, minimum temperature, relative humidity, wind speed, and solar radiation obtained from a meteorological station. • The calculated ETo time series values were decomposed into sub-series using Singular Spectrum Analysis (SSA) to enhance prediction accuracy. • Each sub-series was trained with the first 70% of observations and tested with the remaining 30% via SGB. Final prediction values were obtained by collecting all series predictions. • Three lag times were taken into account during the predictions, and both short-term and long-term ETo values were estimated using the proposed framework. The results were tested with respect to root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) indicators for ensuring whether the model produced statically acceptable outcomes. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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