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Using machine learning to link spatiotemporal information t..:
Kühn, Bernhard
;
Taylor, Marc Hollis
;
Kempf, Alexander
Marine ecology progress series -- Mar Ecol Prog Ser MEPS -- 1616-1599 -- 0171-8630 -- 2022265-8 -- 800780-9. , 2021
Link:
https://doi.org/10.3354/meps13689
RT Journal T1
Using machine learning to link spatiotemporal information to biological processes in the ocean: a case study for North Sea cod recruitment
UL https://suche.suub.uni-bremen.de/peid=base-ftopenagrar:oai:www.openagrar.de:openagrar_mods_00075669&Exemplar=1&LAN=DE A1 Kühn, Bernhard A1 Taylor, Marc Hollis A1 Kempf, Alexander YR 2021 K1 Text K1 ddc:570 K1 Machine learning -- Multi-objective genetic algorithm -- Empirical orthogonal function -- EOF -- Self-organising map -- SOM -- Random forest -- Extreme randomized trees -- Environmental stock-recruitment relationships -- North Sea JF Marine ecology progress series -- Mar Ecol Prog Ser MEPS -- 1616-1599 -- 0171-8630 -- 2022265-8 -- 800780-9 LK http://dx.doi.org/https://doi.org/10.3354/meps13689 DO https://doi.org/10.3354/meps13689 SF ELIB - SuUB Bremen
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