Assessment of Anthropogenic Sources of Potentially Toxic Elements in Soil from Arable Land Using Multivariate Statistical Analysis and Random Forest Analysis
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- Josse, Julie & Husson, François, 2012. "Selecting the number of components in principal component analysis using cross-validation approximations," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1869-1879.
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- Liang Xiao & Yong Zhou & He Huang & Yu-Jie Liu & Ke Li & Meng-Yao Li & Yang Tian & Fei Wu, 2020. "Application of Geostatistical Analysis and Random Forest for Source Analysis and Human Health Risk Assessment of Potentially Toxic Elements (PTEs) in Arable Land Soil," IJERPH, MDPI, vol. 17(24), pages 1-19, December.
- Li Wang & Yong Zhou & Qing Li & Tao Xu & Zhengxiang Wu & Jingyi Liu, 2021. "Application of Three Deep Machine-Learning Algorithms in a Construction Assessment Model of Farmland Quality at the County Scale: Case Study of Xiangzhou, Hubei Province, China," Agriculture, MDPI, vol. 11(1), pages 1-23, January.
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Keywords
arable land; potentially toxic elements; anthropogenic source identification; multivariate statistical analysis; random forest analysis;All these keywords.
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