Machine learning-based modeling of surface water temperature dynamics in arctic lakes

Lake surface-water temperature (LSWT) regulates physical and biochemical processes in lakes. Therefore, understanding the LSWT dynamics is important, especially in Arctic zone since the region is experiencing a warming rate that is greater than the Earth’s average. However, regular measurements of L...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Environmental science and pollution research international 2024-10, Vol.31 (49), p.59642-59655
Hauptverfasser:	Kim, Hyung Il, Kim, Dongkyun, Salamattalab, Mohammad Milad, Mahdian, Mehran, Bateni, Sayed M., Noori, Roohollah
Format:	Artikel
Sprache:	eng
Schlagworte:	Air temperature Algorithms Aquatic Pollution Arctic region Arctic Regions Arctic zone Atmospheric conditions Atmospheric Protection/Air Quality Control/Air Pollution Cloud cover cold zones Earth and Environmental Science Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental Monitoring - methods Lakes Learning algorithms Machine Learning Missing data Modelling Models, Theoretical Neural networks Regression analysis Regression models Remote sensing Research Article Support vector machines Surface temperature Surface water surface water temperature Temperature Waste Water Technology Water Management Water Pollution Control Water temperature
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!