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Detalhes Referência

Tipo
Artigos em Revista

Tipo de Documento
Artigo Completo

Título
Applying Limnological Feature-Based Machine Learning Techniques to Chemical State Classification in Marine Transitional Systems

Participantes na publicação
Ronnie Concepcion (Author)
Elmer Dadios (Author)
Argel Bandala (Author)
Isabel Caçador (Author)
Dep. Biologia Vegetal
MARE
Vanessa F. Fonseca (Author)
Dep. Biologia Animal
MARE
Bernardo Duarte (Author)
Dep. Biologia Vegetal
MARE

Data de Publicação
2021-07-09

Suporte
Frontiers in Marine Science

Identificadores da Publicação
ISSN - 2296-7745

Editora
Frontiers Media SA

Volume
8

Identificadores do Documento
DOI - https://doi.org/10.3389/fmars.2021.658434
URL - http://dx.doi.org/10.3389/fmars.2021.658434

Identificadores de Qualidade
SCOPUS Q1 (2017) - 1.225 - Aquatic Science


Exportar referência

APA
Ronnie Concepcion, Elmer Dadios, Argel Bandala, Isabel Caçador, Vanessa F. Fonseca, Bernardo Duarte, (2021). Applying Limnological Feature-Based Machine Learning Techniques to Chemical State Classification in Marine Transitional Systems. Frontiers in Marine Science, 8, ISSN 2296-7745. eISSN . http://dx.doi.org/10.3389/fmars.2021.658434

IEEE
Ronnie Concepcion, Elmer Dadios, Argel Bandala, Isabel Caçador, Vanessa F. Fonseca, Bernardo Duarte, "Applying Limnological Feature-Based Machine Learning Techniques to Chemical State Classification in Marine Transitional Systems" in Frontiers in Marine Science, vol. 8, 2021. 10.3389/fmars.2021.658434

BIBTEX
@article{52061, author = {Ronnie Concepcion and Elmer Dadios and Argel Bandala and Isabel Caçador and Vanessa F. Fonseca and Bernardo Duarte}, title = {Applying Limnological Feature-Based Machine Learning Techniques to Chemical State Classification in Marine Transitional Systems}, journal = {Frontiers in Marine Science}, year = 2021, volume = 8 }