Support-Vector-Machine-Based Models for Modeling Daily Reference Evapotranspiration With Limited Climatic Data in Extreme Arid Regions
By Xiaohu Wen, Jianhua Si, Zhi-bin He, Jun Wu, H. Shao, Haijiao Yu. Water resources management, 2015
146 citations recorded by the source corpus.
Subfields: Environmental Engineering, Global and Planetary Change, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/9897be84230e0b382ea04531dd70dc4827bc04c1
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In Environmental Engineering
- Mohammad Zounemat‐Kermani
- Behrooz Keshtegar
- Hamed Ghohani Arab
- Ozgur Kisi
- Jan Adamowski
- Kwok-Wing Chau
- Masoud Karbasi
- Ravinesh C. Deo
In Global and Planetary Change
- Mohammad Zounemat‐Kermani
- Hamed Ghohani Arab
- Behrooz Keshtegar
- Ozgur Kisi
- Masoud Karbasi
- Hossein Bonakdari
- Babak Mohammadi
- Babak Jahani
In Water Science and Technology
- Mohammad Zounemat‐Kermani
- Hamed Ghohani Arab
- Behrooz Keshtegar
- Ozgur Kisi
- Masoud Karbasi
- Jan Adamowski
- Ravinesh C. Deo
- Kwok-Wing Chau
Citations in the corpus
- Subset Modeling Basis ANFIS for Prediction of the Reference Evapotranspiration (2018, methodology): “The abilities of support vector machine (SVM) for accurate predictions of the ET0 were compared in references (Wen et al. 2015; Yin et al. 2017).”