Abtew W. (2001). Evaporation estimation for Lake Okeechobee in south Florida. Journal of Irrigation and Drainage Engineering, 127, 140-147.
Akbarzadeh M.S. H., Haghighatjou P. and Bagheri M.H. (2015). Estimates of evaporation from surface water bodies with SEBAL Algorithm using remote sensing techniques (case study: Chahnimeh’s Fresh Water Reservoirs of Sistan). Iranian Journal of Irrigation and Drainage, 3(9), 510-521. (In Farsi)
Bahmani R., Radmanesh F., Islamian S.S. and Parham GH. (2013). Reservoir evaporation trend analysis and its prediction using time series. Journal of Irrigation Sciences and Engineering, 36(3), 67-80. (In Farsi)
Boser B.E., Guyon I.M. and Vapnik V.N. (1992). A training algorithm for optimal margin classifiers. In D.Haussler, editor, 5th Annual ACM Workshop on COLT, Pittsburgh, PA, pp. 144-152.
Chow V. T., Maidment D. R. and Mays L.W. (1988). Applied hydrology. McGraw hill, Newyork, 570 p.
Cohen S., Ianetz A. and Stanhill G. (2002). Evaporative climate changes at bet Dagon, Israel, 1964-1998, Agricultural and Forest Meteorology, 111, 83-91.
Coulomb C.V., legesse D., Gasse F., Travi Y. and Chernet T. (2001). Lake evaporation estimates in tropical Africal (Lake Ziway, Ethiopia). Journal of Hydrology, 245, 1-18.
Dalkilic Y, Okkan U and Baykan N. (2014). Comparison of different ANN approaches in daily pan evaporation prediction. Journal of Water Resource and Protection, 6(4), 319-326.
Fallahi M.R., Varvani H. and Goliyan S. (2012). Precipitation forecasting using regression tree model to flood control. 5th national conference on watershed & soil and water management, Kerman, Iran. (In Farsi)
Gavin H. and Agnew C. A. (2004). Modelling actual reference and equilibrium evaporation from a temperate wet grassland. Hydrological Processes, 18, 229-246.
Ghahreman N. and Gharehkhani A. (2011). Evaluation of random time series models in estimating pan evaporation (case study: Shiraz station). Journal of Water Research in Agriculture, 25(1), 75-81.
Gundekar H. G., Khodke U. M. and Sarkar S. (2008). Evaluation of pan coefficient for reference crop evapotranspiration for semi-arid region. Irrigation Science, 26, 169-175.
Hassan M. (2013). Evaporation estimation for Lake Nasser based on remote sensing technology. Ain Shams Engineering Journal, 4, 593-604.
Khalili Naft Chali A., Khashei Siuki A. and Shahidi A. (2017). Compare KNN and M5 decision tree models in anticipation of evaporation and comparison with empirical equations (Case Study of Birjand). Iranian Journal of Irrigation & Drainage, 11(3), 356-366.
Kuss M. (2006). Gaussian process models for robust regression, classification, and reinforcement learning. Ph. D. dissertation, Technische Universität Darmstadt, Darmstadt, Germany.
Majidi M., Alizadeh A., FaridHosseini A. and Vazifedoust M, (2014). Lake and reservoir evaporation: energy balance estimations, evaluation of combination and radiation- temperature methods. Iranian Journal of Irrigation and Drainage, 3(8), 602-615. (In Farsi)
McGuinness J.L., Bordn, E.F. (1972). A comparson of lysimeterderived potential evapotranspiration with computed values. Technical Bulletin 1452, US Department of Agriculture Agricultural Research Service, Washington, DC.
Mouneskhah V., Majnooni-Heris A. and Fakheri-Fard A. (2018). Evaluation and calibration of empirical relationships for estimating evaporation from free water levels in Urmia Lake Basin. Iranian Journal of Irrigation and Drainage, 5(12), 1281-1291. (In Farsi)
Qasem S., Samadianfard S., Kheshtgar S., Jarhan S., Kisi O., Shamshirband SH. and Wing-Chau K. (2019). Modeling monthly pan evaporation using wavelet support vector regression and wavelet artificial neural networks in arid and humid climates. Engineering Applications of Computational Fluid Mechanics, 13(1), 177-187.
Rosenberry D.O., Winter T.C., Buso D.C., and Likens G.E. (2007). Comparison of 15 evaporation methods applied to a small mountain lake in the northeastern USA. Journal of Hydrology, 340, 149–166.
Samadianfard S., Hashemi S., and Izadyar M. (2018). Estimation of daily pan evaporation by using machine learning methods. Iranian Journal of Irrigation and Drainage, 4(12), 1004-1015. (In Farsi)
Shabani S., Samadianfard S., Sattari M.T., Mosavi A., Shamshirband Sh., Kmet T. and Annamaria R. (2020). Modeling pan evaporation using gaussian process regression k-nearest neighbors random forest and support vector machines; comparative analysis. Atmosphere, 11(66), 1-17.
Sharifazari S. and Araghinejad S. (2013). Develop a non-parametric model to simulate monthly hydrological data. Water and Irrigation Management, 3(1), 83-95. (In Farsi)
Singh D., Ganju A. and Singh A. (2005). Weather prediction using nearest-neighbor model. Current science, 88, 8-25.
Singh A. K., Tripathy R., and Chopra U. K. (2008). Evaluation of CERESWheat and CropSystmodels for water-nitrogen interactions in wheat crop. Agricultural Water Management, 95, 776-786.
Sun Z., Wei B., Su W., Shen W., Wang C., You D and Liu Z. (2011). Evapotranspiration estimation based on the SEBAL model in the Nansi Lake Wetland of China. Mathematical and Computer Modelling, 54(3), 1086-1092.
Tabari H., Marufi S., and Sabziparvar A.A. (2010). Estimation of daily pan evaporation using artificial neural network and multivariate non-linear regression. Irrigation Science, 28(3), 399-406.
Terzi O. (2011). Modeling of daily pan evaporation of Lake Egirdir using data-driven techniques. International symposium on innovations in intelligent systems and Applications, Istanbul, Turkey, pp. 320-324.
Vapnik, V.N. (1995). The Nature of Statistical Learning Theory. Springer, New York. 314 pp.
Vapnik, V.N. (1998). Statistical Learning Theory. Wiley, New York. 736 pp.
Wu X., Kumar V., Quinlan J.R., Ghosh J., Yang Q., Motoda H., McLachlan G.J., Ng A., Liu B. and Philip S.Y. (2008). Top 10 algorithms in data mining. Knowledge and Information Systems, 14, 1–37.