Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security

Future freshwater security relies on hydroclimatic (HC) shifts and regimes for sustainable development. The approximation of the HC system faces major uncertainties and complexities due to the incorporation of heavy datasets, characteristics, and constraints. The proposed study focused on the parall...

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Vydáno v:	Journal of hydroinformatics Ročník 23; číslo 5; s. 950 - 965
Hlavní autoři:	Budamala, Venkatesh, Mahindrakar, Amit Baburao
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London IWA Publishing 01.09.2021
Témata:	adaptive machine learning Adaptive sampling Algorithms Approximation Climatic conditions Community support Emulators Fresh water Freshwater Groundwater hybrid simulators hydroclimatology Hydrology Inland water environment Learning algorithms Machine learning Mathematical analysis Optimization parallel computing Problem solving River basins Rivers Security spatial optimization Surface water Sustainable development Technology Vulnerability Water security Water shortages Water supply Watershed management Watersheds Atlanta Georgia United States > US Chattahoochee River
ISSN:	1464-7141, 1465-1734
On-line přístup:	Získat plný text
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