Developing an optimal individual tree diameter growth model for uneven-aged Pinus yunnanensis forests using machine learning algorithms

The objective of this study was to develop more accurate predictions of the diameter growth of Pinus yunnanensis and to analyze the impact of various factors on its diameter growth, providing valuable management recommendations for forest management. To this end, various machine learning methods wer...

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Vydané v:	Trees (Berlin, West) Ročník 39; číslo 4; s. 58
Hlavní autori:	Deng, Longfeng, Wang, JianMing, Yin, JiTing, Guan, YaDong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2025 Springer Nature B.V
Predmet:	Agriculture Biomedical and Life Sciences China climate Core analysis Forest management Forestry Growth models Impact analysis Learning algorithms Life Sciences Machine learning Multilayer perceptrons neural networks Original Article Pinus yunnanensis Plant Anatomy/Development Plant Pathology Plant Physiology Plant Sciences surveys tree and stand measurements tree growth Trees China Multilayer perceptron and its stacking integration algorithm Random forest XGBoost Diameter growth
ISSN:	0931-1890, 1432-2285
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