Modeling monthly evaporation using two different neural computing techniques

  title={Modeling monthly evaporation using two different neural computing techniques},
  author={{\"O}zg{\"u}r Kisi},
  journal={Irrigation Science},
Two different artificial neural network (ANN) techniques, multi-layer perceptrons (MLP) and radial basis neural networks (RBNN), are employed in the estimation of monthly pan evaporation. The monthly climatic data, air temperature, solar radiation, wind speed, pressure and humidity, of three stations operated by the U.S. Environmental Protection Agency in California are used as inputs to the ANN models to estimate monthly evaporation. In the first part of the study, the accuracy of MLP and RBNN… CONTINUE READING
Highly Cited
This paper has 41 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 16 extracted citations

Daily pan evaporation modeling using linear genetic programming technique

Irrigation Science • 2010
View 11 Excerpts
Method Support
Highly Influenced


Publications referenced by this paper.
Showing 1-10 of 37 references

A comparison of procedures for computing evaporation and evapotranspiration

JC Stephens, EH Stewart
Publication 62, International Association of Scientific Hydrology. International Union of Geodynamics and Geophysics, Berkeley, • 1963
View 5 Excerpts
Highly Influenced

Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (Northern Spain)

G Landeras, A Ortiz-Barredo, JJ López
Agric Water Manage • 2008
View 2 Excerpts

Predicting longitudinal dispersion coefficient in natural streams by artificial intelligence methods

ZF Toprak, HK Cigizoglu
Hydrol Process • 2008
View 2 Excerpts

Testing Reference Evapotranspiration Estimation Methods Using Evaporation Pan and Modeling in Maritime Region of Canada

Z Xing, L Chow, +3 authors S Lionel
J Irrig and Drain Eng • 2008
View 1 Excerpt

Modelling hourly and daily open-water evaporation rates in areas with an equatorial climate

SBK Tan, EB Shuy, LHC Chua
Hydrol Process • 2007
View 2 Excerpts

Artificial neural network models of daily pan evaporation

ME Keskin, O Terzi
ASCE J Hydrol Eng • 2006
View 2 Excerpts

Methods to improve the neural network performance in suspended sediment estimation

HK Cigizoglu, O Kisi
J Hydrol • 2006
View 2 Excerpts

Daily river flow forecasting using artificial neural networks and auto-regressive models

O Kisi
Turk J Eng Environ Sci • 2005
View 2 Excerpts

Flow prediction by three back propagation techniques using k-fold partitioning of neural network training data

HK Cigizoglu, O Kisi
View 2 Excerpts

Suspended sediment estimation using neuro-fuzzy and neural network approaches

O Kisi
Hydrol Sci J • 2005
View 2 Excerpts