NDLI: Modeling of daily pan evaporation of Lake Eğirdir using data-driven techniques

Content Provider	IEEE Xplore Digital Library
Author	Terzi, O.
Copyright Year	2011
Description	Author affiliation: Suleyman Demirel University, Technical Education Faculty, Isparta, 32260 Turkey (Terzi, O.)
Abstract	Gene Expression Programming (GEP) and Radial Basis Function Network (RBFN) models are developed to estimate daily pan evaporation which is an important parameter in hydrological and meteorological studies. Meteorological parameters used to estimate daily pan evaporation from Lake Eğirdir at the southwestern part of Turkey are air temperature (Ta), water temperature (Tw), solar radiation (RC) and relative humidity (Rh). The GEP and RBFN models are developed by using different input combinations with these four parameters. The GEP model with Ta, Tw, RC and Rh parameters has the highest $R^{2}$ (0.812) and the lowest MSE (0.0066 mm/day) values for testing set. The $R^{2}$ value of the best RBFN model is obtained as 0.794 with Ta Tw and Rh. It can be seen that the GEP model was slightly more superior to the RBFN model. It is concluded from the results that GEP and RBFN can be proposed as an alternative to daily pan evaporation measurement.
Starting Page	320
Ending Page	324
File Size	365955
Page Count	5
File Format	PDF
ISBN	9781612849195
e-ISBN	9781612849225
DOI	10.1109/INISTA.2011.5946109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-15
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Radial basis function Neurons Artificial neural networks Daily pan evaporation Lakes Programming Mathematical model Testing Lake Eğirdir Gene expression programming
Content Type	Text
Resource Type	Article

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