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Original Articles

Artificial neural networks for streamflow prediction

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Pages 547-554 | Received 24 May 2001, Published online: 01 Feb 2010

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Read on this site (6)

Ani Shabri & Suhartono. (2012) Streamflow forecasting using least-squares support vector machines. Hydrological Sciences Journal 57:7, pages 1275-1293.
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E. D. Aguero, D. G. Colome & N. V. Granda. (2016) Adjustment of frequency transient response with reserve deficit using artificial neural network. Adjustment of frequency transient response with reserve deficit using artificial neural network.
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Granino A. Korn. 2013. Advanced Dynamic‐System Simulation. Advanced Dynamic‐System Simulation 177 205 .
S. Ismail, A. Shabri & R. Samsudin. (2012) A hybrid model of self organizing maps and least square support vector machine for river flow forecasting. Hydrology and Earth System Sciences 16:11, pages 4417-4433.
Crossref
A.G. Yilmaz, M.A. Imteaz & G. Jenkins. (2011) Catchment flow estimation using Artificial Neural Networks in the mountainous Euphrates Basin. Journal of Hydrology 410:1-2, pages 134-140.
Crossref
R. Samsudin, P. Saad & A. Shabri. (2011) River flow time series using least squares support vector machines. Hydrology and Earth System Sciences 15:6, pages 1835-1852.
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Samira Chabaa, Abdelouhab Zeroual & Jilali Antari. (2011) Application of the MLP neural networks for analyzing non Gaussian signal. Application of the MLP neural networks for analyzing non Gaussian signal.
Lloyd H.C. Chua, Tommy S.W. Wong & X.H. Wang. (2011) Information recovery from measured data by linear artificial neural networks—An example from rainfall–runoff modeling. Applied Soft Computing 11:1, pages 373-381.
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Rabindra K. Panda, Niranjan Pramanik & Biplab Bala. (2010) Simulation of river stage using artificial neural network and MIKE 11 hydrodynamic model. Computers & Geosciences 36:6, pages 735-745.
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Fatih Ünes. (2010) Prediction of Density Flow Plunging Depth in Dam Reservoirs: An Artificial Neural Network Approach. CLEAN – Soil, Air, Water 38:3, pages 296-308.
Crossref
Suhaimi S.Rosmina A. Bustami. (2009) Rainfall Runoff Modeling using Radial Basis Function Neural Network for Sungai Tinjar Catchment, Miri, Sarawak. Journal of Civil Engineering, Science and Technology 1:1, pages 1-7.
Crossref
Aytac GuvenMustafa Gunal. (2008) Prediction of Scour Downstream of Grade-Control Structures Using Neural Networks. Journal of Hydraulic Engineering 134:11, pages 1656-1660.
Crossref
Lloyd H.C. Chua, Tommy S.W. Wong & L.K. Sriramula. (2008) Comparison between kinematic wave and artificial neural network models in event-based runoff simulation for an overland plane. Journal of Hydrology 357:3-4, pages 337-348.
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Alka Sunil Kote & V. Jothiprakash. (2008) Reservoir Inflow Prediction Using Time Lagged Recurrent Neural Networks. Reservoir Inflow Prediction Using Time Lagged Recurrent Neural Networks.
Annie‐Claude Parent, François Anctil, Véronique Cantin & Marie‐Amélie Boucher. (2008) Neural Network Input Selection for Hydrological Forecasting Affected by Snowmelt 1 . JAWRA Journal of the American Water Resources Association 44:3, pages 679-688.
Crossref
A. Sohail, K. Watanabe & S. Takeuchi. (2007) Runoff Analysis for a Small Watershed of Tono Area Japan by Back Propagation Artificial Neural Network with Seasonal Data. Water Resources Management 22:1, pages 1-22.
Crossref
C. Sivapragasam, P. Vincent & G. Vasudevan. (2006) Genetic programming model for forecast of short and noisy data. Hydrological Processes 21:2, pages 266-272.
Crossref
A Güven, M Günal & A Çevik. (2006) Prediction of pressure fluctuations on sloping stilling basins. Canadian Journal of Civil Engineering 33:11, pages 1379-1388.
Crossref
Sung-Uk Choi & Sanghwa Cheong. (2006) PREDICTION OF LOCAL SCOUR AROUND BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS. Journal of the American Water Resources Association 42:2, pages 487-494.
Crossref
Lloyd H. ChuaS. K. Tan. (2005) Use of Artificial Neural Networks as Explicit Finite Difference Operators. Journal of Computing in Civil Engineering 19:4, pages 426-429.
Crossref
. 2005. Hydrologie und Wasserwirtschaft. Hydrologie und Wasserwirtschaft 349 406 .
Marı́a Castellano-Méndez, Wenceslao González-Manteiga, Manuel Febrero-Bande, José Manuel Prada-Sánchez & Román Lozano-Calderón. (2004) Modelling of the monthly and daily behaviour of the runoff of the Xallas river using Box–Jenkins and neural networks methods. Journal of Hydrology 296:1-4, pages 38-58.
Crossref
. (2003) Current awareness. Hydrological Processes 17:16, pages 3379-3381.
Crossref

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