Two hybrid Artificial Intelligence approaches for modeling rainfall–runoff process
Top Cited Papers
- 13 May 2011
- journal article
- Published by Elsevier BV in Journal of Hydrology
- Vol. 402 (1-2), 41-59
- https://doi.org/10.1016/j.jhydrol.2011.03.002
Abstract
No abstract availableKeywords
This publication has 42 references indexed in Scilit:
- Estimation and forecasting of daily suspended sediment data using wavelet–neural networksJournal of Hydrology, 2008
- Development of a short-term river flood forecasting method for snowmelt driven floods based on wavelet and cross-wavelet analysisJournal of Hydrology, 2008
- Wavelet and neuro-fuzzy conjunction model for precipitation forecastingJournal of Hydrology, 2007
- Recent advances in wavelet analyses: Part 1. A review of conceptsJournal of Hydrology, 2005
- A neuro-fuzzy computing technique for modeling hydrological time seriesJournal of Hydrology, 2004
- Time series forecasting using a hybrid ARIMA and neural network modelNeurocomputing, 2003
- Rainfall–runoff relations for karstic springs. Part II: continuous wavelet and discrete orthogonal multiresolution analysesJournal of Hydrology, 2000
- Evaluating the use of “goodness‐of‐fit” Measures in hydrologic and hydroclimatic model validationWater Resources Research, 1999
- An artificial neural network approach to rainfall-runoff modellingHydrological Sciences Journal, 1998
- Comparison of univariate and transfer function models of groundwater fluctuationsWater Resources Research, 1993