Modelling of total dissolved solids in water supply systems using regression and supervised machine learning approaches

Modelling of total dissolved solids in water supply systems using regression and supervised machine learning approaches

Abstract Monitoring of water quality through accurate predictions provides adequate information about water management. In the present study, three different modelling approaches: Gaussian process regression (GPR), backpropagation neural network (BPNN) and principal component regression (PCR) models...

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Bibliographic Details
Main Authors: Anthony Ewusi, Isaac Ahenkorah, Derrick Aikins
Format: Article
Language:English
Published: SpringerOpen 2021-01-01
Series:Applied Water Science
Subjects:
Water quality
Total dissolved solids
Artificial neural network
Principal component regression
Online Access:https://doi.org/10.1007/s13201-020-01352-7

Internet

https://doi.org/10.1007/s13201-020-01352-7

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