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

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...

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Bibliographic Details
Main Authors: Kangjie Sun, Mohammad Rajabtabar, Seyedehzahra Samadi, Mohammad Rezaie-Balf, Alireza Ghaemi, Shahab S. Band, Amir Mosavi
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
water pollution
multivariate adaptive regression splines
crow search algorithm
artificial intelligence
machine learning
Online Access:http://dx.doi.org/10.1080/19942060.2020.1861987

Internet

http://dx.doi.org/10.1080/19942060.2020.1861987

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