2024
DOI: 10.20944/preprints202403.0627.v1
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Application Of Machine Learning To Understand Pfas Occurrence, Distribution, Transport And Removal In Water

Adewale Ajao

Abstract: Per- and polyfluoroalkyl substances (PFAS) are arguably the most common water contaminants in the world today. While several research experiments have been done to understand and remove PFAS from the environment, there is still a lot of unknown. Little has been known about the use of Machine learning (ML) to understand PFAS. This work hence reviews some leading ML approaches and applications in PFAS studies in the distribution, transport, removal, and occurrence predictions of PFAS. Several evaluation matrices… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 46 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?