Identification study of soil types based on feature factors of XRF spectrum combining with machine learning-Reference-Cited by-同舟云学术

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Identification study of soil types based on feature factors of XRF spectrum combining with machine learning

Published:2024-09 Issue: Volume:219 Page:107001
ISSN:0584-8547
Container-title:Spectrochimica Acta Part B: Atomic Spectroscopy
language:en
Short-container-title:Spectrochimica Acta Part B: Atomic Spectroscopy

Author:

Wang Ying,Gan Tingting,Zhao Nanjing,Yin Gaofang,Ye Ziqi,Sheng Ruoyu,Li Tanghu,Liang Tianhong,Jia Renqing,Fang Li,Hu Xiang,Li Xingchi

Funder

National Natural Science Foundation of China

National Key Scientific Instrument and Equipment Development Projects of China

Publisher

Elsevier BV

Reference46 articles.

1. Spatiotemporal variation of soil heavy metals in China: the pollution status and risk assessment;Shi;Sci. Total Environ.,2023

2. Integrated survey on the heavy metal distribution, sources and risk assessment of soil in a commonly developed industrial area;Lei;Ecotoxicol. Environ. Saf.,2022

3. Current status and temporal trend of heavy metals in farmland soil of the Yangtze River Delta region: field survey and meta-analysis;Diwei Shao;Environ. Pollut.,2016

4. A comprehensive survey on the horizontal and vertical distribution of heavy metals and microorganisms in soils of a Pb /Zn smelter;Li;J. Hazard. Mater.,2020

5. Source analysis and source-oriented risk assessment of heavy metal pollution in agricultural soils of different cultivated land qualities;Fei;J. Clean. Prod.,2022

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