منابع
[1].Tokar AS, Markus M. Precipitation – runoff modeling using artificialneural network and conceptual models. Journal of Hydrologic Engineering. 2000;4:150-161.
[2].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]
[3].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]
[4].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.
[5].Chua HC, and Wong SW. Rainfall-runoff modeling using artificial neural network coupled with singular spectrum analysis. JournalHydrology. 2011. 399: 394-409.
[6].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.
[7].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]
[8].Braddock RD,Kremmer ML, Sanzogni L. Feedforward artificial neural network model forforecasting rainfall-runoff. Journal of Environmental Sciences. 1998. 9:419-432.
[9]. Kia M. Soft Computing in MATLAB.Qian academic publishing. [Persian]
[10].www.mathwork.com
[11].Demuth H,Beale M. Neural network toolbox for use with MATLAB. Sixth printing Revised for Version 4. Pp:680.
[12].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]
[13]. 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.
[14].Cybenko G. Approximation by superposition of a sigmoidal function. Mathematics of control, signals and systems 2.4. 1989. 303-314.
[15].Hornik K, Stinchcombe M, White H. Multilayer feed-forward networks are universal approximators. Neural Networks. 1989. 2(5):359-366.
[16].Zhang G, Patuwo BE, Hu MY. Forecasting with artificial neural networks: the state of the art. International Journalof Forecasting. 1998. 14(1):35-62.
[18].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]
[19].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
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