Application of fractal-wavelet analysis for separation of geochemical anomalies
The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Ba...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Afzal, Peyman [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Schlagwörter: |
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| Umfang: |
10 |
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| Übergeordnetes Werk: |
Enthalten in: Moving beyond the employee: The role of the organizational context in leader workplace aggression - Sharma, Payal Nangia ELSEVIER, 2017, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:128 ; year:2017 ; pages:27-36 ; extent:10 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.jafrearsci.2016.08.017 |
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ELV014830582 |
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| 520 | |a The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. | ||
| 520 | |a The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. | ||
| 650 | 7 | |a Decomposed wavelet transformation (DWT) |2 Elsevier | |
| 650 | 7 | |a Geochemical anomaly |2 Elsevier | |
| 650 | 7 | |a Morlet wavelet |2 Elsevier | |
| 650 | 7 | |a Fractal-wavelet analysis |2 Elsevier | |
| 650 | 7 | |a Daubechies wavelet |2 Elsevier | |
| 700 | 1 | |a Ahmadi, Kamyar |4 oth | |
| 700 | 1 | |a Rahbar, Kambiz |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Sharma, Payal Nangia ELSEVIER |t Moving beyond the employee: The role of the organizational context in leader workplace aggression |d 2017 |g Amsterdam [u.a.] |w (DE-627)ELV002200333 |
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10.1016/j.jafrearsci.2016.08.017 doi GBVA2017003000011.pica (DE-627)ELV014830582 (ELSEVIER)S1464-343X(16)30279-5 DE-627 ger DE-627 rakwb eng 550 550 DE-600 300 330 360 VZ 85.05 bkl 85.06 bkl 89.52 bkl Afzal, Peyman verfasserin aut Application of fractal-wavelet analysis for separation of geochemical anomalies 2017transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. Decomposed wavelet transformation (DWT) Elsevier Geochemical anomaly Elsevier Morlet wavelet Elsevier Fractal-wavelet analysis Elsevier Daubechies wavelet Elsevier Ahmadi, Kamyar oth Rahbar, Kambiz oth Enthalten in Elsevier Science Sharma, Payal Nangia ELSEVIER Moving beyond the employee: The role of the organizational context in leader workplace aggression 2017 Amsterdam [u.a.] (DE-627)ELV002200333 volume:128 year:2017 pages:27-36 extent:10 https://doi.org/10.1016/j.jafrearsci.2016.08.017 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.05 Betriebssoziologie Betriebspsychologie VZ 85.06 Unternehmensführung VZ 89.52 Politische Psychologie Politische Soziologie VZ AR 128 2017 27-36 10 045F 550 |
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10.1016/j.jafrearsci.2016.08.017 doi GBVA2017003000011.pica (DE-627)ELV014830582 (ELSEVIER)S1464-343X(16)30279-5 DE-627 ger DE-627 rakwb eng 550 550 DE-600 300 330 360 VZ 85.05 bkl 85.06 bkl 89.52 bkl Afzal, Peyman verfasserin aut Application of fractal-wavelet analysis for separation of geochemical anomalies 2017transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. Decomposed wavelet transformation (DWT) Elsevier Geochemical anomaly Elsevier Morlet wavelet Elsevier Fractal-wavelet analysis Elsevier Daubechies wavelet Elsevier Ahmadi, Kamyar oth Rahbar, Kambiz oth Enthalten in Elsevier Science Sharma, Payal Nangia ELSEVIER Moving beyond the employee: The role of the organizational context in leader workplace aggression 2017 Amsterdam [u.a.] (DE-627)ELV002200333 volume:128 year:2017 pages:27-36 extent:10 https://doi.org/10.1016/j.jafrearsci.2016.08.017 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.05 Betriebssoziologie Betriebspsychologie VZ 85.06 Unternehmensführung VZ 89.52 Politische Psychologie Politische Soziologie VZ AR 128 2017 27-36 10 045F 550 |
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10.1016/j.jafrearsci.2016.08.017 doi GBVA2017003000011.pica (DE-627)ELV014830582 (ELSEVIER)S1464-343X(16)30279-5 DE-627 ger DE-627 rakwb eng 550 550 DE-600 300 330 360 VZ 85.05 bkl 85.06 bkl 89.52 bkl Afzal, Peyman verfasserin aut Application of fractal-wavelet analysis for separation of geochemical anomalies 2017transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. Decomposed wavelet transformation (DWT) Elsevier Geochemical anomaly Elsevier Morlet wavelet Elsevier Fractal-wavelet analysis Elsevier Daubechies wavelet Elsevier Ahmadi, Kamyar oth Rahbar, Kambiz oth Enthalten in Elsevier Science Sharma, Payal Nangia ELSEVIER Moving beyond the employee: The role of the organizational context in leader workplace aggression 2017 Amsterdam [u.a.] (DE-627)ELV002200333 volume:128 year:2017 pages:27-36 extent:10 https://doi.org/10.1016/j.jafrearsci.2016.08.017 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.05 Betriebssoziologie Betriebspsychologie VZ 85.06 Unternehmensführung VZ 89.52 Politische Psychologie Politische Soziologie VZ AR 128 2017 27-36 10 045F 550 |
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10.1016/j.jafrearsci.2016.08.017 doi GBVA2017003000011.pica (DE-627)ELV014830582 (ELSEVIER)S1464-343X(16)30279-5 DE-627 ger DE-627 rakwb eng 550 550 DE-600 300 330 360 VZ 85.05 bkl 85.06 bkl 89.52 bkl Afzal, Peyman verfasserin aut Application of fractal-wavelet analysis for separation of geochemical anomalies 2017transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. Decomposed wavelet transformation (DWT) Elsevier Geochemical anomaly Elsevier Morlet wavelet Elsevier Fractal-wavelet analysis Elsevier Daubechies wavelet Elsevier Ahmadi, Kamyar oth Rahbar, Kambiz oth Enthalten in Elsevier Science Sharma, Payal Nangia ELSEVIER Moving beyond the employee: The role of the organizational context in leader workplace aggression 2017 Amsterdam [u.a.] (DE-627)ELV002200333 volume:128 year:2017 pages:27-36 extent:10 https://doi.org/10.1016/j.jafrearsci.2016.08.017 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.05 Betriebssoziologie Betriebspsychologie VZ 85.06 Unternehmensführung VZ 89.52 Politische Psychologie Politische Soziologie VZ AR 128 2017 27-36 10 045F 550 |
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10.1016/j.jafrearsci.2016.08.017 doi GBVA2017003000011.pica (DE-627)ELV014830582 (ELSEVIER)S1464-343X(16)30279-5 DE-627 ger DE-627 rakwb eng 550 550 DE-600 300 330 360 VZ 85.05 bkl 85.06 bkl 89.52 bkl Afzal, Peyman verfasserin aut Application of fractal-wavelet analysis for separation of geochemical anomalies 2017transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. Decomposed wavelet transformation (DWT) Elsevier Geochemical anomaly Elsevier Morlet wavelet Elsevier Fractal-wavelet analysis Elsevier Daubechies wavelet Elsevier Ahmadi, Kamyar oth Rahbar, Kambiz oth Enthalten in Elsevier Science Sharma, Payal Nangia ELSEVIER Moving beyond the employee: The role of the organizational context in leader workplace aggression 2017 Amsterdam [u.a.] (DE-627)ELV002200333 volume:128 year:2017 pages:27-36 extent:10 https://doi.org/10.1016/j.jafrearsci.2016.08.017 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.05 Betriebssoziologie Betriebspsychologie VZ 85.06 Unternehmensführung VZ 89.52 Politische Psychologie Politische Soziologie VZ AR 128 2017 27-36 10 045F 550 |
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application of fractal-wavelet analysis for separation of geochemical anomalies |
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Application of fractal-wavelet analysis for separation of geochemical anomalies |
| abstract |
The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. |
| abstractGer |
The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. |
| abstract_unstemmed |
The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area. |
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However, the main targets for detailed exploration is located in the central part of the studied area.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Decomposed wavelet transformation (DWT)</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Geochemical anomaly</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Morlet wavelet</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Fractal-wavelet analysis</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Daubechies wavelet</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ahmadi, Kamyar</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rahbar, Kambiz</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Sharma, Payal Nangia ELSEVIER</subfield><subfield code="t">Moving beyond the employee: The role of the organizational context in leader workplace aggression</subfield><subfield code="d">2017</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV002200333</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:128</subfield><subfield code="g">year:2017</subfield><subfield code="g">pages:27-36</subfield><subfield code="g">extent:10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.jafrearsci.2016.08.017</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">85.05</subfield><subfield code="j">Betriebssoziologie</subfield><subfield code="j">Betriebspsychologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">85.06</subfield><subfield code="j">Unternehmensführung</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">89.52</subfield><subfield code="j">Politische Psychologie</subfield><subfield code="j">Politische Soziologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">128</subfield><subfield code="j">2017</subfield><subfield code="h">27-36</subfield><subfield code="g">10</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">550</subfield></datafield></record></collection>
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