SENSITIVE ANALYSIS OF METEOROLOGICAL DATA AND SELECTING APPROPRIATE MACHINE LEARNING MODEL FOR ESTIMATION OF REFERENCE EVAPOTRANSPIRATION

Sensitive analysis of meteorological data and selecting appropriate machine learning model for estimation of reference evapotranspiration

Abstract This study applies three methods, Gene Expression Programming (GEP), M5 tree (M5T) model and optimized Artificial Neural Network by Genetic Algorithm (ANN-GA) for estimation of reference evapotranspiration in Ahvaz and Dezful in the southwest of Iran.Comparison between results of the FAO Penman-Monteith (FPM) method and the mentioned three

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