Modeling reference evapotranspiration using three different heuristic regression approaches
By Ozgur Kisi. 2016
129 citations recorded by the source corpus.
Subfields: Environmental Engineering, Global and Planetary Change, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/bb9dba982cadb36c90d8f7524787f24cdf97e191
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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 Ocean Engineering
Citations in the corpus
- Subset Modeling Basis ANFIS for Prediction of the Reference Evapotranspiration (2018, methodology): “In addition to ANNs, several ANFIS models, which are based on fuzzy logic concepts in the soft computing techniques have been applied to evapotranspiration modeling (Citakoglu et al. 2014; Cobaner 2011; Dogan 2009; Kisi 2016; Kisi and Zounemat-Kermani 2014; Petković et al. 2015; Pour-Ali Baba et al.”
- Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment (2018, unknown): “…(MARS) and M5 model tree (M5Tree) are also two main data-driven models, which have been used in many fields, such as pan evaporation estimation (Kisi 2015, 2016, Rahimikhoob et al. 2013), drought forecasting (Choubin et al. 2016; Deo et al. 2017a), Big Data (Zhang et al. 2016b), river flow…”