Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

Bibliographic Details
Published in:Ecological Informatics
Main Authors: Fernandes, Jose A., Irigoien, Xabier, Lozano, Jose A., Inza, Iñaki, Goikoetxea, Nerea, Pérez, Aritz
Other Authors: Fundación Centros Tecnológicos Iñaki Goenaga, Department of Agriculture, Fisheries and Food of the Basque Country Government, Saiotek and Research Groups 2007–2012, Basque Government, Spanish Ministry of Education and Science, COMBIOMED network in computational biomedicine (Carlos III Health Institute), EU project UNCOVER, EU FACT, EU VII Framework project MEECE
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier BV 2015
Subjects:
Applied Mathematics
Computational Theory and Mathematics
Computer Science Applications
Ecological Modeling
Modeling and Simulation
Ecology
Ecology, Evolution, Behavior and Systematics
North East Atlantic
Online Access:http://dx.doi.org/10.1016/j.ecoinf.2014.11.004
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spelling crelsevierbv:10.1016/j.ecoinf.2014.11.004 2023-09-05T13:21:47+02:00 Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species Fernandes, Jose A. Irigoien, Xabier Lozano, Jose A. Inza, Iñaki Goikoetxea, Nerea Pérez, Aritz Fundación Centros Tecnológicos Iñaki Goenaga Department of Agriculture Fisheries and Food of the Basque Country Government Saiotek and Research Groups 2007–2012 Basque Government Spanish Ministry of Education and Science COMBIOMED network in computational biomedicine (Carlos III Health Institute) EU project UNCOVER EU FACT EU VII Framework project MEECE 2015 http://dx.doi.org/10.1016/j.ecoinf.2014.11.004 https://api.elsevier.com/content/article/PII:S1574954114001563?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S1574954114001563?httpAccept=text/plain en eng Elsevier BV https://www.elsevier.com/tdm/userlicense/1.0/ Ecological Informatics volume 25, page 35-42 ISSN 1574-9541 Applied Mathematics Computational Theory and Mathematics Computer Science Applications Ecological Modeling Modeling and Simulation Ecology Ecology, Evolution, Behavior and Systematics journal-article 2015 crelsevierbv https://doi.org/10.1016/j.ecoinf.2014.11.004 2023-08-23T16:47:57Z Article in Journal/Newspaper North East Atlantic ScienceDirect (Elsevier - via Crossref) Ecological Informatics 25 35 42
institution Open Polar
collection ScienceDirect (Elsevier - via Crossref)
op_collection_id crelsevierbv
language English
topic Applied Mathematics
Computational Theory and Mathematics
Computer Science Applications
Ecological Modeling
Modeling and Simulation
Ecology
Ecology, Evolution, Behavior and Systematics
spellingShingle Applied Mathematics
Computational Theory and Mathematics
Computer Science Applications
Ecological Modeling
Modeling and Simulation
Ecology
Ecology, Evolution, Behavior and Systematics
Fernandes, Jose A.
Irigoien, Xabier
Lozano, Jose A.
Inza, Iñaki
Goikoetxea, Nerea
Pérez, Aritz
Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species
topic_facet Applied Mathematics
Computational Theory and Mathematics
Computer Science Applications
Ecological Modeling
Modeling and Simulation
Ecology
Ecology, Evolution, Behavior and Systematics
author2 Fundación Centros Tecnológicos Iñaki Goenaga
Department of Agriculture
Fisheries and Food of the Basque Country Government
Saiotek and Research Groups 2007–2012
Basque Government
Spanish Ministry of Education and Science
COMBIOMED network in computational biomedicine (Carlos III Health Institute)
EU project UNCOVER
EU FACT
EU VII Framework project MEECE
format Article in Journal/Newspaper
author Fernandes, Jose A.
Irigoien, Xabier
Lozano, Jose A.
Inza, Iñaki
Goikoetxea, Nerea
Pérez, Aritz
author_facet Fernandes, Jose A.
Irigoien, Xabier
Lozano, Jose A.
Inza, Iñaki
Goikoetxea, Nerea
Pérez, Aritz
author_sort Fernandes, Jose A.
title Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species
title_short Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species
title_full Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species
title_fullStr Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species
title_full_unstemmed Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species
title_sort evaluating machine-learning techniques for recruitment forecasting of seven north east atlantic fish species
publisher Elsevier BV
publishDate 2015
url http://dx.doi.org/10.1016/j.ecoinf.2014.11.004
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genre North East Atlantic
genre_facet North East Atlantic
op_source Ecological Informatics
volume 25, page 35-42
ISSN 1574-9541
op_rights https://www.elsevier.com/tdm/userlicense/1.0/
op_doi https://doi.org/10.1016/j.ecoinf.2014.11.004
container_title Ecological Informatics
container_volume 25
container_start_page 35
op_container_end_page 42
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