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Predicting the vessel lumen area tree-ring parameter of Quercus robur with linear and nonlinear machine learning algorithms Cover

Predicting the vessel lumen area tree-ring parameter of Quercus robur with linear and nonlinear machine learning algorithms

Geochronometria
Volume 45 (2018): Issue 1 (January 2018)
By: Jernej Jevšenak,  Sašo Džeroski and  Tom Levanič  
Open Access
|Nov 2018

Authors

Jernej Jevšenak

Slovenian Forestry Institute, Department of Forest Yield and Silviculture, Ljubljana, Slovenia

Sašo Džeroski

Jožef Stefan Institute, Department of Knowledge Technologies, Ljubljana, Slovenia
Jožef Stefan International Postgraduate School, Ljubljana, Slovenia

Tom Levanič

tom.levanic@gozdis.si

Slovenian Forestry Institute, Department of Forest Yield and Silviculture, Ljubljana, Slovenia
DOI: https://doi.org/10.1515/geochr-2015-0097 | Journal eISSN: 1897-1695
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Language: English
Page range: 211 - 222
Submitted on: Jan 26, 2018
|
Accepted on: Aug 28, 2018
|
Published on: Nov 5, 2018
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
dendroclimatology,
artificial neural networks,
multiple linear regression,
machine learning,
vessel lumen area,
Quercus robur
Related subjects:
Geosciences,
Geosciences, other

© 2018 Jernej Jevšenak, Sašo Džeroski, Tom Levanič, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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