Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model

Lai Simin; Wan Li; Zeng Xiangjian

doi:doi:10.11648/j.ijdst.20190501.14

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Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model

Lai Simin, Wan Li, Zeng Xiangjian

Published in International Journal on Data Science and Technology (Volume 5, Issue 1)

Received: 12 April 2019 Published: 23 May 2019

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Abstract

The self-similarity of ore-forming elements is caused by long-term, multi-period characteristics and the abnormal fluctuation induced by emergency in geological process. In this study, the fractal jump model referred as a combination of fractional Brownian motion and Poisson distributed jumps was built to depict the fluctuation pattern of ore-forming elements and simulate the distribution of Au sequence for three different mineralization intensities in Dayingezhuang gold deposit in the Jiaodong gold province, China. By calculating the fitting error and drawing the comparison diagram between the simulated data and the actual data, the applicability and advantages of the model were verified. The results showed that the fractal jump model can be considered as a reliable and computationally efficient method through the comparison of the statistical characteristics between simulated and real data. In addition, this model can well depict the change of the Au element content sequence, and better simulation was achieved when the intensity of mineralization was higher. The present work provides a new insight on the prediction of mineralized levels in concealed orebody.

Published in	International Journal on Data Science and Technology (Volume 5, Issue 1)
DOI	10.11648/j.ijdst.20190501.14
Page(s)	29-34
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Ore-Forming Elements, Fractional Brownian Motion, Poisson Distribution

References

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APA Style

Lai Simin, Wan Li, Zeng Xiangjian. (2019). Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model. International Journal on Data Science and Technology, 5(1), 29-34. https://doi.org/10.11648/j.ijdst.20190501.14

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ACS Style

Lai Simin; Wan Li; Zeng Xiangjian. Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model. Int. J. Data Sci. Technol. 2019, 5(1), 29-34. doi: 10.11648/j.ijdst.20190501.14

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AMA Style

Lai Simin, Wan Li, Zeng Xiangjian. Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model. Int J Data Sci Technol. 2019;5(1):29-34. doi: 10.11648/j.ijdst.20190501.14

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@article{10.11648/j.ijdst.20190501.14,
  author = {Lai Simin and Wan Li and Zeng Xiangjian},
  title = {Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model},
  journal = {International Journal on Data Science and Technology},
  volume = {5},
  number = {1},
  pages = {29-34},
  doi = {10.11648/j.ijdst.20190501.14},
  url = {https://doi.org/10.11648/j.ijdst.20190501.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20190501.14},
  abstract = {The self-similarity of ore-forming elements is caused by long-term, multi-period characteristics and the abnormal fluctuation induced by emergency in geological process. In this study, the fractal jump model referred as a combination of fractional Brownian motion and Poisson distributed jumps was built to depict the fluctuation pattern of ore-forming elements and simulate the distribution of Au sequence for three different mineralization intensities in Dayingezhuang gold deposit in the Jiaodong gold province, China. By calculating the fitting error and drawing the comparison diagram between the simulated data and the actual data, the applicability and advantages of the model were verified. The results showed that the fractal jump model can be considered as a reliable and computationally efficient method through the comparison of the statistical characteristics between simulated and real data. In addition, this model can well depict the change of the Au element content sequence, and better simulation was achieved when the intensity of mineralization was higher. The present work provides a new insight on the prediction of mineralized levels in concealed orebody.},
 year = {2019}
}

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TY  - JOUR
T1  - Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model
AU  - Lai Simin
AU  - Wan Li
AU  - Zeng Xiangjian
Y1  - 2019/05/23
PY  - 2019
N1  - https://doi.org/10.11648/j.ijdst.20190501.14
DO  - 10.11648/j.ijdst.20190501.14
T2  - International Journal on Data Science and Technology
JF  - International Journal on Data Science and Technology
JO  - International Journal on Data Science and Technology
SP  - 29
EP  - 34
PB  - Science Publishing Group
SN  - 2472-2235
UR  - https://doi.org/10.11648/j.ijdst.20190501.14
AB  - The self-similarity of ore-forming elements is caused by long-term, multi-period characteristics and the abnormal fluctuation induced by emergency in geological process. In this study, the fractal jump model referred as a combination of fractional Brownian motion and Poisson distributed jumps was built to depict the fluctuation pattern of ore-forming elements and simulate the distribution of Au sequence for three different mineralization intensities in Dayingezhuang gold deposit in the Jiaodong gold province, China. By calculating the fitting error and drawing the comparison diagram between the simulated data and the actual data, the applicability and advantages of the model were verified. The results showed that the fractal jump model can be considered as a reliable and computationally efficient method through the comparison of the statistical characteristics between simulated and real data. In addition, this model can well depict the change of the Au element content sequence, and better simulation was achieved when the intensity of mineralization was higher. The present work provides a new insight on the prediction of mineralized levels in concealed orebody.
VL  - 5
IS  - 1
ER  -

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Author Information

Lai Simin

School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
Wan Li

School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
Zeng Xiangjian

School of Mathematics and Information Science, Guangzhou University, Guangzhou, China

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Plain Text BibTeX RIS

APA Style

Lai Simin, Wan Li, Zeng Xiangjian. (2019). Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model. International Journal on Data Science and Technology, 5(1), 29-34. https://doi.org/10.11648/j.ijdst.20190501.14

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ACS Style

Lai Simin; Wan Li; Zeng Xiangjian. Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model. Int. J. Data Sci. Technol. 2019, 5(1), 29-34. doi: 10.11648/j.ijdst.20190501.14

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AMA Style

Lai Simin, Wan Li, Zeng Xiangjian. Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model. Int J Data Sci Technol. 2019;5(1):29-34. doi: 10.11648/j.ijdst.20190501.14

Copy | Download

@article{10.11648/j.ijdst.20190501.14,
  author = {Lai Simin and Wan Li and Zeng Xiangjian},
  title = {Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model},
  journal = {International Journal on Data Science and Technology},
  volume = {5},
  number = {1},
  pages = {29-34},
  doi = {10.11648/j.ijdst.20190501.14},
  url = {https://doi.org/10.11648/j.ijdst.20190501.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20190501.14},
  abstract = {The self-similarity of ore-forming elements is caused by long-term, multi-period characteristics and the abnormal fluctuation induced by emergency in geological process. In this study, the fractal jump model referred as a combination of fractional Brownian motion and Poisson distributed jumps was built to depict the fluctuation pattern of ore-forming elements and simulate the distribution of Au sequence for three different mineralization intensities in Dayingezhuang gold deposit in the Jiaodong gold province, China. By calculating the fitting error and drawing the comparison diagram between the simulated data and the actual data, the applicability and advantages of the model were verified. The results showed that the fractal jump model can be considered as a reliable and computationally efficient method through the comparison of the statistical characteristics between simulated and real data. In addition, this model can well depict the change of the Au element content sequence, and better simulation was achieved when the intensity of mineralization was higher. The present work provides a new insight on the prediction of mineralized levels in concealed orebody.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Fluctuation Analysis to Sequence of Ore-forming Element Based on Fractal-Jump Model
AU  - Lai Simin
AU  - Wan Li
AU  - Zeng Xiangjian
Y1  - 2019/05/23
PY  - 2019
N1  - https://doi.org/10.11648/j.ijdst.20190501.14
DO  - 10.11648/j.ijdst.20190501.14
T2  - International Journal on Data Science and Technology
JF  - International Journal on Data Science and Technology
JO  - International Journal on Data Science and Technology
SP  - 29
EP  - 34
PB  - Science Publishing Group
SN  - 2472-2235
UR  - https://doi.org/10.11648/j.ijdst.20190501.14
AB  - The self-similarity of ore-forming elements is caused by long-term, multi-period characteristics and the abnormal fluctuation induced by emergency in geological process. In this study, the fractal jump model referred as a combination of fractional Brownian motion and Poisson distributed jumps was built to depict the fluctuation pattern of ore-forming elements and simulate the distribution of Au sequence for three different mineralization intensities in Dayingezhuang gold deposit in the Jiaodong gold province, China. By calculating the fitting error and drawing the comparison diagram between the simulated data and the actual data, the applicability and advantages of the model were verified. The results showed that the fractal jump model can be considered as a reliable and computationally efficient method through the comparison of the statistical characteristics between simulated and real data. In addition, this model can well depict the change of the Au element content sequence, and better simulation was achieved when the intensity of mineralization was higher. The present work provides a new insight on the prediction of mineralized levels in concealed orebody.
VL  - 5
IS  - 1
ER  -

Copy | Download