Application of hybrid machine learning models and data pre-processing to predict water level of watersheds: Recent trends and future perspective

The community's well-being and economic livelihoods are heavily influenced by the water level of watersheds. The changes in water levels directly affect the circulation processes of lakes and rivers that control water mixing and bottom sediment resuspension, further affecting water quality and...

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Vydané v:	Cogent engineering Ročník 9; číslo 1
Hlavní autori:	Mohammed, Sarah J., Zubaidi, Salah L., Ortega-Martorell, Sandra, Al-Ansari, Nadhir, Ethaib, Saleem, Hashim, Khalid
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Cogent 31.12.2022 Taylor & Francis Ltd Taylor & Francis Group
Predmet:	Algorithms data pre-processing Environment models Geoteknik hybrid model Lakes Machine learning meta-heuristic algorithms Monitoring Optimization Parameters Research methodology Soil Mechanics Water circulation Water level fluctuations Water level forecasting Water levels Water quality Watersheds
ISSN:	2331-1916, 2331-1916
On-line prístup:	Získať plný text
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