Suspended Sediment Modeling Using a Heuristic Regression Method Hybridized with Kmeans Clustering

The accurate estimation of suspended sediments (SSs) carries significance in determining the volume of dam storage, river carrying capacity, pollution susceptibility, soil erosion potential, aquatic ecological impacts, and the design and operation of hydraulic structures. The presented study propose...

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Vydané v:	Sustainability Ročník 13; číslo 9; s. 4648
Hlavní autori:	Adnan, Rana Muhammad, Parmar, Kulwinder Singh, Heddam, Salim, Shahid, Shamsuddin, Kisi, Ozgur
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.05.2021
Predmet:	Accuracy Algorithms Case studies Clustering Dams Freshwater resources Hydrology Machine learning Mars Methods Neural networks Rivers Sediment transport Sediment, Suspended Soil erosion Stream flow Success Support vector machines Sustainability United States > US
ISSN:	2071-1050, 2071-1050
On-line prístup:	Získať plný text
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