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Employing a Probabilistic Neural Network for Classifying Cyprus Coastal Eutrophication Status

Employing a Probabilistic Neural Network for Classifying Cyprus Coastal Eutrophication Status

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6dba972d0b9c4b10bd67c2033d3ef202

Employing a Probabilistic Neural Network for Classifying Cyprus Coastal Eutrophication Status

About this item

Full title

Employing a Probabilistic Neural Network for Classifying Cyprus Coastal Eutrophication Status

Publisher

Les Ulis: EDP Sciences

Journal title

E3S web of conferences, 2024-01, Vol.585, p.9007

Language

English

Formats

Publication information

Publisher

Les Ulis: EDP Sciences

More information

Scope and Contents

Contents

Good coastal water quality is important for human well-being but also for marine organisms. The European Water Framework Directive (2000/60/EC) has established threshold values for regional seas, with Cyprus collaborating with Greece to assess conditions and set common chlorophyll-a (chl-a) thresholds. In the Levantine Basin, known for its oligotro...

Alternative Titles

Full title

Employing a Probabilistic Neural Network for Classifying Cyprus Coastal Eutrophication Status

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_6dba972d0b9c4b10bd67c2033d3ef202

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6dba972d0b9c4b10bd67c2033d3ef202

Other Identifiers

ISSN

2267-1242,2555-0403

E-ISSN

2267-1242

DOI

10.1051/e3sconf/202458509007

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