Efficient Water Quality Prediction Using Supervised Machine Learning

Water makes up about 70% of the earth’s surface and is one of the most important sources vital to sustaining life. Rapid urbanization and industrialization have led to a deterioration of water quality at an alarming rate, resulting in harrowing diseases. Water quality has been conventionally estimat...

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Bibliographic Details
Published in:	Water (Basel) Vol. 11; no. 11; p. 2210
Main Authors:	Ahmed, Umair, Mumtaz, Rafia, Anwar, Hirra, Shah, Asad A., Irfan, Rabia, García-Nieto, José
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.11.2019
Subjects:	Algorithms Analysis artificial intelligence Chemical oxygen demand Data mining Datasets Detectors Developing countries harrowing industrialization LDCs Literature reviews Machine learning monitoring motivation Neural networks prediction regression analysis Sensors temperature total dissolved solids Tropical diseases turbidity urbanization Water quality Pakistan
ISSN:	2073-4441, 2073-4441
Online Access:	Get full text
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