A combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the Dashui ore-concentration district, Central China
Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (w...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wang, Xinhua [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019transfer abstract |
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| Umfang: |
10 |
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| Übergeordnetes Werk: |
Enthalten in: Sizing of hybrid electric propulsion system for retrofitting a mid-scale aircraft using non-dominated sorting genetic algorithm - Xie, Ye ELSEVIER, 2018, JGE : official journal of the Association of Exploration Geochemists, Amsterdam |
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| Übergeordnetes Werk: |
volume:197 ; year:2019 ; pages:228-237 ; extent:10 |
| Links: |
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| DOI / URN: |
10.1016/j.gexplo.2018.12.008 |
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| 520 | |a Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. | ||
| 520 | |a Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. | ||
| 700 | 1 | |a Liu, Jiajun |4 oth | |
| 700 | 1 | |a Carranza, Emmanuel John M. |4 oth | |
| 700 | 1 | |a Wang, Jiaxin |4 oth | |
| 700 | 1 | |a Wang, Gongwen |4 oth | |
| 700 | 1 | |a Zhai, Degao |4 oth | |
| 700 | 1 | |a Yuan, Qingzheng |4 oth | |
| 700 | 1 | |a Shi, Wenquan |4 oth | |
| 700 | 1 | |a Zhang, Jiangsu |4 oth | |
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10.1016/j.gexplo.2018.12.008 doi GBV00000000000470.pica (DE-627)ELV045303312 (ELSEVIER)S0375-6742(18)30064-5 DE-627 ger DE-627 rakwb eng 620 VZ 55.50 bkl 55.60 bkl 55.60 bkl Wang, Xinhua verfasserin aut A combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the Dashui ore-concentration district, Central China 2019transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Liu, Jiajun oth Carranza, Emmanuel John M. oth Wang, Jiaxin oth Wang, Gongwen oth Zhai, Degao oth Yuan, Qingzheng oth Shi, Wenquan oth Zhang, Jiangsu oth Enthalten in Elsevier Science Xie, Ye ELSEVIER Sizing of hybrid electric propulsion system for retrofitting a mid-scale aircraft using non-dominated sorting genetic algorithm 2018 JGE : official journal of the Association of Exploration Geochemists Amsterdam (DE-627)ELV000984752 volume:197 year:2019 pages:228-237 extent:10 https://doi.org/10.1016/j.gexplo.2018.12.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 55.50 Luftfahrzeugtechnik VZ 55.60 Raumfahrttechnik VZ 55.60 Raumfahrttechnik VZ AR 197 2019 228-237 10 |
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10.1016/j.gexplo.2018.12.008 doi GBV00000000000470.pica (DE-627)ELV045303312 (ELSEVIER)S0375-6742(18)30064-5 DE-627 ger DE-627 rakwb eng 620 VZ 55.50 bkl 55.60 bkl 55.60 bkl Wang, Xinhua verfasserin aut A combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the Dashui ore-concentration district, Central China 2019transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Liu, Jiajun oth Carranza, Emmanuel John M. oth Wang, Jiaxin oth Wang, Gongwen oth Zhai, Degao oth Yuan, Qingzheng oth Shi, Wenquan oth Zhang, Jiangsu oth Enthalten in Elsevier Science Xie, Ye ELSEVIER Sizing of hybrid electric propulsion system for retrofitting a mid-scale aircraft using non-dominated sorting genetic algorithm 2018 JGE : official journal of the Association of Exploration Geochemists Amsterdam (DE-627)ELV000984752 volume:197 year:2019 pages:228-237 extent:10 https://doi.org/10.1016/j.gexplo.2018.12.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 55.50 Luftfahrzeugtechnik VZ 55.60 Raumfahrttechnik VZ 55.60 Raumfahrttechnik VZ AR 197 2019 228-237 10 |
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10.1016/j.gexplo.2018.12.008 doi GBV00000000000470.pica (DE-627)ELV045303312 (ELSEVIER)S0375-6742(18)30064-5 DE-627 ger DE-627 rakwb eng 620 VZ 55.50 bkl 55.60 bkl 55.60 bkl Wang, Xinhua verfasserin aut A combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the Dashui ore-concentration district, Central China 2019transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Liu, Jiajun oth Carranza, Emmanuel John M. oth Wang, Jiaxin oth Wang, Gongwen oth Zhai, Degao oth Yuan, Qingzheng oth Shi, Wenquan oth Zhang, Jiangsu oth Enthalten in Elsevier Science Xie, Ye ELSEVIER Sizing of hybrid electric propulsion system for retrofitting a mid-scale aircraft using non-dominated sorting genetic algorithm 2018 JGE : official journal of the Association of Exploration Geochemists Amsterdam (DE-627)ELV000984752 volume:197 year:2019 pages:228-237 extent:10 https://doi.org/10.1016/j.gexplo.2018.12.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 55.50 Luftfahrzeugtechnik VZ 55.60 Raumfahrttechnik VZ 55.60 Raumfahrttechnik VZ AR 197 2019 228-237 10 |
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10.1016/j.gexplo.2018.12.008 doi GBV00000000000470.pica (DE-627)ELV045303312 (ELSEVIER)S0375-6742(18)30064-5 DE-627 ger DE-627 rakwb eng 620 VZ 55.50 bkl 55.60 bkl 55.60 bkl Wang, Xinhua verfasserin aut A combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the Dashui ore-concentration district, Central China 2019transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Liu, Jiajun oth Carranza, Emmanuel John M. oth Wang, Jiaxin oth Wang, Gongwen oth Zhai, Degao oth Yuan, Qingzheng oth Shi, Wenquan oth Zhang, Jiangsu oth Enthalten in Elsevier Science Xie, Ye ELSEVIER Sizing of hybrid electric propulsion system for retrofitting a mid-scale aircraft using non-dominated sorting genetic algorithm 2018 JGE : official journal of the Association of Exploration Geochemists Amsterdam (DE-627)ELV000984752 volume:197 year:2019 pages:228-237 extent:10 https://doi.org/10.1016/j.gexplo.2018.12.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 55.50 Luftfahrzeugtechnik VZ 55.60 Raumfahrttechnik VZ 55.60 Raumfahrttechnik VZ AR 197 2019 228-237 10 |
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10.1016/j.gexplo.2018.12.008 doi GBV00000000000470.pica (DE-627)ELV045303312 (ELSEVIER)S0375-6742(18)30064-5 DE-627 ger DE-627 rakwb eng 620 VZ 55.50 bkl 55.60 bkl 55.60 bkl Wang, Xinhua verfasserin aut A combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the Dashui ore-concentration district, Central China 2019transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. Liu, Jiajun oth Carranza, Emmanuel John M. oth Wang, Jiaxin oth Wang, Gongwen oth Zhai, Degao oth Yuan, Qingzheng oth Shi, Wenquan oth Zhang, Jiangsu oth Enthalten in Elsevier Science Xie, Ye ELSEVIER Sizing of hybrid electric propulsion system for retrofitting a mid-scale aircraft using non-dominated sorting genetic algorithm 2018 JGE : official journal of the Association of Exploration Geochemists Amsterdam (DE-627)ELV000984752 volume:197 year:2019 pages:228-237 extent:10 https://doi.org/10.1016/j.gexplo.2018.12.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 55.50 Luftfahrzeugtechnik VZ 55.60 Raumfahrttechnik VZ 55.60 Raumfahrttechnik VZ AR 197 2019 228-237 10 |
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a combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the dashui ore-concentration district, central china |
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A combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the Dashui ore-concentration district, Central China |
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Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. |
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Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. |
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Sometimes geochemical anomalies linked with buried mineral deposits are too weak to be recognized by conventional methods. In this study, element concentration data from a stream sediment survey were subjected to a combined method of SWPCA (spatially-weighted principal components analysis) and WT (wavelet transformation) to derive a geochemical anomaly model for epithermal Au deposits in the Dashui ore-concentration district. The SWPCA was applied as a data integration method to extract information related to mineralization in the geochemical data. The WT was applied as a powerful tool for recognizing mineralization related anomalies in a complex geochemical field and for enhancing weak anomalies from background. The SWPCA–WT geochemical anomaly model indicated high favorability values for the known mineral occurrences and out-performed PCA–WT and SWPCA models. The SWPCA–WT geochemical model generated in this study provides a robust guide for further gold exploration in the Dashui ore-concentration district. |
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A combined approach using spatially-weighted principal components analysis and wavelet transformation for geochemical anomaly mapping in the Dashui ore-concentration district, Central China |
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