Modeling Pan Evaporation Using Gaussian Process Regression K-Nearest Neighbors Random Forest and Support Vector Machines; Comparative Analysis

Modeling Pan Evaporation Using Gaussian Process Regression K-Nearest Neighbors Random Forest and Support Vector Machines; Comparative Analysis

Evaporation is a very important process; it is one of the most critical factors in agricultural, hydrological, and meteorological studies. Due to the interactions of multiple climatic factors, evaporation is considered as a complex and nonlinear phenomenon to model. Thus, machine learning methods ha...

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Bibliographic Details
Main Authors: Sevda Shabani, Saeed Samadianfard, Mohammad Taghi Sattari, Amir Mosavi, Shahaboddin Shamshirband, Tibor Kmet, Annamária R. Várkonyi-Kóczy
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Atmosphere
Subjects:
machine learning
meteorological parameters
pan evaporation
advanced statistical analysis
hydrological cycle
big data
hydroinformatics
random forest (rf)
support vector regression (svr)
Online Access:https://www.mdpi.com/2073-4433/11/1/66

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