Publisher
Springer Science and Business Media LLC
Subject
General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering
Reference50 articles.
1. Abebe AJ, Price RK (2003) Managing uncertainty in hydrological models using complementary models. Hydrol Sci J 48(5):679–692. https://doi.org/10.1623/hysj.48.5.679.51450
2. Abebe AJ, Price RK (2004) Information theory and neural networks for managing uncertainty in flood routing. J Comput Civ Eng 18(4):373–380. https://doi.org/10.1061/(ASCE)0887-3801(2004)18:4(373)
3. Ayzel G (2019) Does deep learning advance hourly runoff predictions. In: Proceedings of the V international conference information technologies and high-performance computing (ITHPC-2019), Khabarovsk, Russia, pp. 16–19
4. Ba H, Guo S, Wang Y, Hong X, Zhong Y, Liu Z (2018) Improving ANN model performance in runoff forecasting by adding soil moisture input and using data preprocessing techniques. Hydrol Res 49(3):744–760. https://doi.org/10.2166/nh.2017.048
5. Badrzadeh H, Sarukkalige R, Jayawardena AW (2015) Hourly runoff forecasting for flood risk management: application of various computational intelligence models. J Hydrol 529:1633–1643. https://doi.org/10.1016/j.jhydrol.2015.07.057
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