Predicting Soil Available Phosphorus by Hyperspectral Regression Method Based on Gradient Boosting Decision Tree-Reference-Cited by-同舟云学术

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Predicting Soil Available Phosphorus by Hyperspectral Regression Method Based on Gradient Boosting Decision Tree

Published:2019 Issue:13 Volume:56 Page:131102
ISSN:1006-4125
Container-title:Laser & Optoelectronics Progress
language:en
Short-container-title:激光与光电子学进展

Author:

Xiu Jin 金秀,Xianzhi Zhu 朱先志,Shaowen Li 李绍稳,Wencai Wang 王文才,Haijun Qi 齐海军

Publisher

Shanghai Institute of Optics and Fine Mechanics

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning and genetic algorithm for mapping soil available phosphorus in coastal provinces in Southeast China;Ecological Indicators;2024-09

2. Modelling Soil Ammonium Nitrogen, Nitrate Nitrogen and Available Phosphorus Using Normalized Difference Vegetation Index and Climate Data in Xizang’s Grasslands;Sustainability;2024-05-31

3. Estimation of generalized soil structure index based on differential spectra of different orders by multivariate assessment;International Soil and Water Conservation Research;2023-08

4. Mapping of Soil pH Based on SVM-RFE Feature Selection Algorithm;Agronomy;2022-11-04

5. Efficient Machine Learning Models for the Uplift Behavior of Helical Anchors in Dense Sand for Wind Energy Harvesting;Applied Sciences;2022-10-15

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