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Updated: Jun 3, 2026

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
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Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

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基于自然因素的空间预测和中国表面土壤中典型重金属的来源分配:机器学习模型的应用

Jin Chao1, Huangling Gu1, Qinpeng Liao1

  • 1School of Metallurgy and Environment, Central South University, Changsha, 410083, China; Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution, Changsha, 410083, China.

Environmental pollution (Barking, Essex : 1987)
|December 9, 2024
PubMed
概括

机器学习模型准确地预测土壤中的重金属 (HM) 分布,识别地质和土壤特性等关键自然因素. 这有助于了解污染风险,并为环境管理策略提供信息.

关键词:
重金属是一种重金属.机器学习是机器学习.自然资源的分配自然资源的分配.空间分布的空间分布

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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...