Binary Grey Wolf Optimization-Regularized Extreme Learning Machine Wrapper Coupled with the Boruta Algorithm for Monthly Streamflow Forecasting
- 31 January 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Water Resources Management
- Vol. 35 (3), 1029-1045
- https://doi.org/10.1007/s11269-021-02770-1
Abstract
No abstract availableKeywords
Funding Information
- Doctoral Research Fund of North China University of Water Resources and Electric Power (40464)
This publication has 50 references indexed in Scilit:
- Short-Term Streamflow Forecasting Using the Feature-Enhanced Regression ModelWater Resources Management, 2019
- Streamflow regionalization using a similarity approach in ungauged basins: Application of the geo-environmental signatures in the Karkheh River Basin, IranCATENA, 2019
- Stream Flow Forecasting of Poorly Gauged Mountainous Watershed by Least Square Support Vector Machine, Fuzzy Genetic Algorithm and M5 Model Tree Using Climatic Data from Nearby StationWater Resources Management, 2018
- Robustness of Extreme Learning Machine in the prediction of hydrological flow seriesComputers & Geosciences, 2018
- Monthly Streamflow Forecasting Using EEMD-Lasso-DBN Method Based on Multi-Scale Predictors SelectionWater, 2018
- The CAMELS data set: catchment attributes and meteorology for large-sample studiesHydrology and Earth System Sciences, 2017
- Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literatureGeoscientific Model Development, 2014
- A survey on feature selection methodsComputers and Electrical Engineering, 2014
- Generalization performance of support vector machines and neural networks in runoff modelingExpert Systems with Applications, 2009
- Evolutionary artificial neural networks for hydrological systems forecastingJournal of Hydrology, 2009