Enhancing XGBoost’s accuracy in soil organic matter prediction through feature fusion-Reference-Cited by-同舟云学术

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Enhancing XGBoost’s accuracy in soil organic matter prediction through feature fusion

Published:2024-06-04 Issue:3 Volume:22 Page:475-489
ISSN:1611-2490
Container-title:Paddy and Water Environment
language:en
Short-container-title:Paddy Water Environ

Author:

He Shaofang^ORCID,Zhou Li,Xie Hongxia,Tan Siqiao

Funder

Natural Science Foundation of Hunan Province

Scientific Research Program of Hunan Province Department of Education

National Science and Technology Basic Work Special Project

Changsha Soft Science Research Program

Excellent Youth Program of Hunan Provincial Department of Education

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10333-024-00980-y.pdf

Reference33 articles.

1. Afriyie E, Verdoodt V, Mouazen AM (2021) Data fusion of visible near-infrared and mid-infrared spectroscopy for rapid estimation of soil aggregate stability indices. Comput Electron Agric 187:106229. https://doi.org/10.1016/j.compag.2021.106229

2. Ai TH (2021) Some thoughts on deep learning enabling cartography. Acta Geod et Cartogr Sin 50(9):1170–1182. https://doi.org/10.24294/jgc.v5i2.1670

3. Allo M, Todoroff P, Jameux M et al (2020) Prediction of tropical volcanic soil organic carbon stocks by visible-near- and mid-infrared spectroscopy. Catena 189:104452. https://doi.org/10.1016/j.catena.2020.104452

4. Cao R, Liao B, Li M et al (2021) Predicting prices and analyzing features of online short-term rentals based on XGBoost. Data Anal Knowl Discov 5(6):51–65. https://doi.org/10.11925/infotech.2096-3467.2020.1186

5. Cao YY, Yang W, Li H et al (2024) Development of a vehicle-mounted soil organic matter detection system based on near-infrared spectroscopy and image information fusion. Measure Sci Technol 35(4):5501. https://doi.org/10.1088/1361-6501/ad179f

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