Reservoir Inflow Modeling Using Temporal Neural Networks with Forgetting Factor Approach
Author:
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
http://link.springer.com/content/pdf/10.1007/s11269-008-9263-7.pdf
Reference25 articles.
1. Ahmed JA, Sarma AK (2007) ‘Artificial neural network model for synthetic streamflow generation. Water Resour Manage 21(6):1015–1029, Springer Netherlands
2. Altunkaynak A (2007) Forecasting surface water level fluctuations of Lake Van by artificial neural networks. Water Resour Manage 21(2):399–408, Springer Netherlands
3. Anmala J, Zhang B, Govindaraju RS (2000) Comparison of ANNs and empirical approaches for predicting watershed runoff. J Water Resour Plng Mgmt ASCE 126(3):156–166
4. Araghinejad S, Burn DH, Karamouz M (2006) Long-lead streamflow forecasting using ocean-atmospheric and hydrological predictors. Water Resour Res 42(3):W03431, DOI 10.1029/2004WR003853
5. Atiya A, Parlos A (1992) Nonlinear system identification using spatiotemporal neural networks. In Proc. Intl. Joint Conf. on neural networks, Baltimore, MD, vol. 2, pp. 504–509, The IEEE, Inc., Piscataway, NJ
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