Evolutionary and ensemble machine learning predictive models for evaluation of water quality
Authors:
- Ali AldreesAAAli Aldrees
- Muhammad Faisal JavedMJMuhammad Faisal Javed
- Abubakr Taha Bakheit TahaATAbubakr Taha Bakheit Taha
- Abdeliazim Mustafa MohamedAMAbdeliazim Mustafa Mohamed
- Michał JasińskiMJMichał Jasiński
- Miroslava GonoMGMiroslava Gono
Open Access
- 7 February 2023
- journal article
- research article
- Published by Elsevier in Journal of Hydrology: Regional Studies
- Vol. 46
Abstract
No abstract availableKeywords
This publication has 60 references indexed in Scilit:
- Application of artificial neural networks and mathematical modeling for the prediction of water quality variables (case study: southwest of Iran)Desalination and Water Treatment, 2016
- Effects of Irrigation with Saline Water on Crop Growth and Yield in Greenhouse CultivationWater, 2016
- A novel hybrid water quality time series prediction method based on cloud model and fuzzy forecastingChemometrics and Intelligent Laboratory Systems, 2015
- Design equations for prediction of pressuremeter soil deformation moduli utilizing expression programming systemsNeural Computing and Applications, 2012
- Modeling snowmelt-runoff under climate scenarios in the Hunza River basin, Karakoram Range, Northern PakistanJournal of Hydrology, 2011
- Estimation of predictive hydrological uncertainty using quantile regression: examples from the National Flood Forecasting System (England and Wales)Hydrology and Earth System Sciences, 2011
- A data mining approach to compressive strength of CFRP-confined concrete cylindersSTRUCTURAL ENGINEERING AND MECHANICS, 2010
- Multi expression programming: a new approach to formulation of soil classificationEngineering with Computers, 2009
- Random forests as a tool for ecohydrological distribution modellingEcological Modelling, 2007
- Machine learning approaches for estimation of prediction interval for the model outputNeural Networks, 2006