Using Advanced Machine-Learning Algorithms to Estimate the Site Index of Masson Pine Plantations

Using Advanced Machine-Learning Algorithms to Estimate the Site Index of Masson Pine Plantations

The rapid development of non-parametric machine learning methods, such as random forest (RF), extreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM), provide new methods to predict the site index (SI). However, few studies used these methods for SI modeling of Masson...

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Bibliographic Details
Main Authors: Rui Yang, Jinghui Meng
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Forests
Subjects:
site index
dominant height
soil chemistry
machine learning
XGBoost
LightGBM
Online Access:https://www.mdpi.com/1999-4907/13/12/1976

Internet

https://www.mdpi.com/1999-4907/13/12/1976

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