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Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers
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SYSNO 0570811 Title Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers Author(s) Kuhl, E. (DE)
Zang, C. (DE)
Esper, Jan (UEK-B) [VS1] SAI, ORCID, RID
Riechelmann, D. F. C. (DE)
Büntgen, Ulf (UEK-B) [VS1] RID, ORCID, SAI
Briesch, M. (DE)
Reinig, F. (DE)
Roemer, P. (DE)
Konter, O. (DE)
Schmidhalter, M. (CH)
Hartl, C. (DE)Source Title Ecosphere . Roč. 14, č. 3 (2023). - : Wiley Article number e4453 Document Type Článek v odborném periodiku Grant EF16_019/0000797 GA MŠMT - Ministry of Education, Youth and Sports (MEYS), CZ - Czech Republic Institutional support UEK-B - RVO:86652079 Language eng Country US Keywords artificial intelligence * dendrochronology * dendroprovenancing * European Alps * Extreme Gradient Boosting * Larix decidua * tree-ring density * tree-ring width Cooperating institutions Masarykova univerzita Brno (Czech Republic) URL https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecs2.4453 Permanent Link https://hdl.handle.net/11104/0342148 File Download Size Commentary Version Access Kuhl-2023-Using-machine-learning-on-treering-.pdf 8 2.2 MB Publisher’s postprint open-access
Number of the records: 1