Tracking Major Sources of Water Contamination Using Machine Learning

Tracking Major Sources of Water Contamination Using Machine Learning

Current microbial source tracking techniques that rely on grab samples analyzed by individual endpoint assays are inadequate to explain microbial sources across space and time. Modeling and predicting host sources of microbial contamination could add a useful tool for watershed management. In this s...

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Bibliographic Details
Main Authors: Jianyong Wu, Conghe Song, Eric A. Dubinsky, Jill R. Stewart
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-01-01
Series:Frontiers in Microbiology
Subjects:
machine learning
XGBoost
fecal contamination
microbial source tracking
land use
rainfall
Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2020.616692/full

Internet

https://www.frontiersin.org/articles/10.3389/fmicb.2020.616692/full

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