Machine learning ensemble technique for exploring soil type evolution.

Saved in:
Bibliographic Details
Title: Machine learning ensemble technique for exploring soil type evolution.
Authors: Wu X; School of Public Affairs, Institute of Land Science and Property, Zhejiang University, Hangzhou, 310058, China., Wu K; School of Land Science and Technology, China University of Geosciences, Beijing, 100083, China.; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing, 100035, China., Hao S; School of Land Science and Technology, China University of Geosciences, Beijing, 100083, China., Yu E; School of Public Affairs, Institute of Land Science and Property, Zhejiang University, Hangzhou, 310058, China., Zhao J; School of Public Affairs, Institute of Land Science and Property, Zhejiang University, Hangzhou, 310058, China., Li Y; School of Public Affairs, Institute of Land Science and Property, Zhejiang University, Hangzhou, 310058, China. liyan522@zju.edu.cn.
Source: Scientific reports [Sci Rep] 2025 Jul 07; Vol. 15 (1), pp. 24332. Date of Electronic Publication: 2025 Jul 07.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
Description
ISSN:2045-2322
DOI:10.1038/s41598-025-10608-8