Prediction of Water Quality through Dissolved Oxygen Saturation using Data Mining: A Case Study of Puebla Mexico
Year: 2024
Type: article
Abstract: Computational sciences have been highlighted in the application to any area with good results. One of the primary interests of humanity is water quality because it is a vital resource for the existence of living beings. This research applies a data mining model based on CRISP-DM methodology built to classify water contamination in lotic systems in Puebla City, located in the center of Mexico. The classification was carried out through physicochemical parameters using a water quality evaluation model based on the amount of dissolved oxygen percentage (%DO). Results demonstrate that the application of decision trees and K-NN algorithms, using chemical parameters, are effective in determining the presence of contamination in lotic water bodies and represent a novel way to evaluate water quality in the water system along rivers in Puebla, Mexico.
Authors: Claudia Denicia Carral, G. Jafet Yáñez García, Ana L. Ballinas Hernández, Gustavo M. Minquiz Xolo
Institution: Benemérita Universidad Autónoma de Puebla
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404852414