An integrated machine learning, noise suppression, and population-based algorithm to improve total dissolved solids prediction

Monitoring the water contaminants is of utmost importance in water resource management. Prediction of the total dissolved solid (TDS) is particularly essential for water quality management and planning in the areas exposed to a mixture of pollutants. TDS primarily includes inorganic minerals and org...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Engineering applications of computational fluid mechanics Ročník 15; číslo 1; s. 251 - 271
Hlavní autoři:	Sun, Kangjie, Rajabtabar, Mohammad, Samadi, Seyedehzahra, Rezaie-Balf, Mohammad, Ghaemi, Alireza, Band, Shahab S., Mosavi, Amir
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Hong Kong Taylor & Francis 01.01.2021 Taylor & Francis Ltd Taylor & Francis Group
Témata:	Algorithms artificial intelligence Contaminants crow search algorithm Dissolved solids Evolutionary algorithms Gaging stations Heuristic methods Machine learning Mathematical models multivariate adaptive regression splines Noise reduction Optimization Parameters Pollutants Quality management Search algorithms Supervised learning water pollution Water quality Water resources management
ISSN:	1994-2060, 1997-003X
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!