2022
DOI: 10.1016/j.gexplo.2021.106924
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Integrating principal component analysis and U-statistics for mapping polluted areas in mining districts

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Cited by 5 publications
(2 citation statements)
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“…Principal component analysis aims to transform multiple indicators into a few composite indicators (i.e., principal components) using the idea of dimensionality reduction, and each principal component is used to analyze and interpret the information contained in the original data indicators [8,9,29,30]. In order to identify the sources of major elements in geothermal fluids, the eight indicators of Ca 2+ , Mg 2+ , Na + , K + , Cl − , SO 4 2− , HCO 3 − , and H 2 SiO 3 of eight geothermal water samples were subjected to principal component analysis in this study.…”
Section: Ion Source Analysis 421 Principal Component Analysismentioning
confidence: 99%
“…Principal component analysis aims to transform multiple indicators into a few composite indicators (i.e., principal components) using the idea of dimensionality reduction, and each principal component is used to analyze and interpret the information contained in the original data indicators [8,9,29,30]. In order to identify the sources of major elements in geothermal fluids, the eight indicators of Ca 2+ , Mg 2+ , Na + , K + , Cl − , SO 4 2− , HCO 3 − , and H 2 SiO 3 of eight geothermal water samples were subjected to principal component analysis in this study.…”
Section: Ion Source Analysis 421 Principal Component Analysismentioning
confidence: 99%
“…Each principal component is extracted to explain the information of the raw data variables. The principal component contribution scores can explain the geospatial distribution and temporal variation characteristics of the raw hydrochemical data [25][26][27].…”
Section: Principal Component Analysismentioning
confidence: 99%