AYLIK BUHARLAŞMA TAHMİNİNDE YAPAY ZEKA YÖNTEMLERİNİN KULLANILABİLİRLİĞİ

Ayşe Özel; Meral Büyükyıldız

doi:10.28948/ngumuh.516891

Research Article

USABILITY OF ARTIFICIAL INTELLIGENCE METHODS FOR ESTIMATION OF MONTHLY EVAPORATION

Year 2019, , 244 - 254, 28.01.2019

Ayşe Özel Meral Büyükyıldız

https://doi.org/10.28948/ngumuh.516891

Cited By: 4

Abstract

Evaporation, one of the most
important components of the hydrological cycle, is influenced by many factors.
Evaporation is a meteorological parameter that is difficult to predict due to
this complex structure. In this study, the amount of monthly evaporation was
estimated using different input combinations formed by meteorological
parameters belonging to Karaman station in Konya Closed Basin. For this
purpose, Artificial Neural Networks (ANN), Support Vector Regression (SVR),
Adaptive Network Based Fuzzy Inference System (ANFIS) methods are used. As a
result, SVR has been more successful than other methods in monthly evaporation
prediction.

Keywords

Evaporation, artificial neural networks, support vector regression, water resources

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