.Tokar AS, Markus M. Precipitation – runoff modeling using artificialneural network and conceptual models. Journal of Hydrologic Engineering. 2000;4:150-161.
.Razavi SS, Karamuoz M. in Prediction monthly river flows by using artificial aeural network. 10th studentsConferenceonCivil Engineering. Amirkabir University of Technology. 22 Oct 2003. [Persian]
.Fathi P, Mohammadi Y, Homayi M. Intelligent modeling of monthly flow time series into vahdat dam in sanandaj city. Journal of Water and Soil. 2009; 23(1):209-220. [Persian]
.Dorum A, Yarar A, FaikSevimli M, and Onucyildiz M. Modelling the rainfall-runoff data of susurluk basin. Expert Systems with Applications. 2010. 37: 6587-6593.
.Chua HC, and Wong SW. Rainfall-runoff modeling using artificial neural network coupled with singular spectrum analysis. JournalHydrology. 2011. 399: 394-409.
.Patil S,Valunjkar, S. Study of different rainfall-runoff forecasting algorithms for better water consumption. International Conference on Computational Techniques and Artificial Intelligence. 2012. 327-330.
.Zeynali MJ, Nikbakht S, Mohammadezapour O. Prediction Input Flows to Mollasadra Reservoir by Useing Artificial Neural Network. 5th Iranian water resources management conference. ShahidbeheshtiUniversity.29 jul 2013. [Persian]
.Braddock RD,Kremmer ML, Sanzogni L. Feedforward artificial neural network model forforecasting rainfall-runoff. Journal of Environmental Sciences. 1998. 9:419-432.
. Kia M. Soft Computing in MATLAB.Qian academic publishing. [Persian]
.Demuth H,Beale M. Neural network toolbox for use with MATLAB. Sixth printing Revised for Version 4. Pp:680.
.Hahangeer AR, Raeini M, Ahmadi MZ. Comparison of artificial neural networks (ANN) simulation of rainfall-runoff process with HEC-HMS model in Kardeh watershed. Journal of Water and Soil. 2008. 22(2):72-84. [Persian]
. Kumar S, Merwade V, Kam J, Thurner K. Streamflow trends in Indiana: effects of long term persistence, precipitation and subsurface drains. Journal of Hydrology. 2009.374(1): 171-183.
.Cybenko G. Approximation by superposition of a sigmoidal function. Mathematics of control, signals and systems 2.4. 1989. 303-314.
.Hornik K, Stinchcombe M, White H. Multilayer feed-forward networks are universal approximators. Neural Networks. 1989. 2(5):359-366.
.Zhang G, Patuwo BE, Hu MY. Forecasting with artificial neural networks: the state of the art. International Journalof Forecasting. 1998. 14(1):35-62.
.Nikmanesh MR. Prediction of Monthly Average Discharge Using the Hybrid Model of Artificial Neural Network and Wavelet Transforms (Case Study: Kor River Pol-e-Khan Station). Journal of Water and Soil Conservation. 2015. 22(3):231-239. [Persian]
.Noori R, Farokhnia A, Morid S, RiahiMadvar H. Effect of Input Variables Preprocessing in Artificial Neural Network on Monthly Flow Prediction by PCA and Wavelet Transformation. Journal of Water & Wastewater. 2008. 20(69):1-22