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IJSEA Archive (Volume 7, Issue 4)

International Journal of Science and Engineering Applications (IJSEA)  (Volume 7, Issue 4 April 2018)

Exploration Geochemistry Data-Application for Cu Anomaly Separation Based On Classical and Modern Statistical Methods in South Khorasan, Iran

Aref Shirazi, Ardeshir Hezarkhani , Adel Shirazy





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Keywords: FCM; SOM; K-Means; Classical statistics; Anomaly separation; Exploration geochemistry; Copper

Abstract References BibText


        The polymetal mining area is located 30 kilometers northwest of Birjand, South Khorasan Province of Iran. Considering the importance of recognizing the geochemical limit value for post-analysis studies, the limit value (= non-normative visualization) in the data of the stream was identified and described using the classic and modern statistical method. Sampling method in this area was lithogeochemical samples. Simple statistical methods, K-Means, K-Medoids, Fuzzy C-Mean (FCM), Self-Organized Map (SOM), have been used in this study. Anomaly maps are depicted in each method and separated from the background. Each method showed different anomalies, but the K-Mean and K-Medoids methods had similar responses.


[1] Hasani Pak, A.A., Sharafodin, M. (2012). Exploration data analysis. University of Tehran Publication. Tehran.
[2] Govett, G. J. S., Goodfellow, W. D., Chapman, R. P., & Chork, C. Y. (1975). Exploration geochemistry-distribution of elements and recognition of anomalies. Journal of the International Association for Mathematical Geology, 7 (5-6), 415 - 446. https://doi.org/10.1007/ BF02080498
[3] Emami, M. H. (1972). Geology and petrological investigation on Shahkuh volcanic rocks, south of Birjand, eastern Iran. University of Tehran, Tehran, Iran.
[4] Walker, R. T., & Khatib, M. M. (2006). Active faulting in the Birjand region of NE Iran. Tectonics, 25(4).
[5] Hoseinpoor, M. K., & Aryafar, A. (2016). Using robust staged R-mode factor analysis and logistic function to identify probable Cu-mineralization zones in Khusf 1: 100,000 sheets, east of Iran. Arabian Journal of Geosciences, 9(2), 157. https://doi.org/10.1007/s12517-015-2266-9
[6] Aghanabati, A. (2004). Geology of Iran. Geological survey of Iran.
[7] Ghorbani, M. (2002). An introduction to economic geology of Iran. Tehran, Iran. Geological survey and mineral explorations of Iran (in Persian).
[8] Vahdati Daneshmand, F. (1989). 1: 100,000 Geology Map of Khusf, Geological survey of Iran.
[9] de Mulder, E. F., Cheng, Q., Agterberg, F., & Goncalves, M. (2016). New and game-changing developments in geochemical exploration. Episodes, 39(1), 70-71. http://dx.doi.org/10.22059/ijmge.2014.53107
[10] Journel, A. G., & Huijbregts, C. J. (1978). Mining geostatistics. Academic press.
[11] Howell, D. C. (2014). Median absolute deviation. Wiley StatsRef: Statistics Reference Online.
[12] Twain, M., & Weather, N. E. (2004). Mean Absolute Deviation. Dynamic Portfolio Theory and Management, 235. https://doi.org/10.1287/mnsc.37.5.519
[13] Likas, A., Vlassis, N., & Verbeek, J. J. (2003). The global k-means clustering algorithm. Pattern recognition, 36(2), 451-461. https://doi.org/10.1016/S0031-3203(02)00060-2
[14] Hartigan, J. A., & Wong, M. A. (1979). Algorithm AS 136: A k-means clustering algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics), 28(1), 100-108. http://dx.doi.org/10.2307/2346830
[15] Park, H. S., & Jun, C. H. (2009). A simple and fast algorithm for K-medoids clustering. Expert systems with applications, 36(2), 3336-3341. https://doi.org/10.1016/j.eswa.2008.01.039
[16] Sohaib, M., & Mushtaq, Q. (2013). Dimensional Reduction of Hyperspectral Image DataUsing Band Clustering and Selection Based on Statistical Characteristics of Band Images. International Journal of Computer and Communication Engineering, 2(2), 101. http://dx.doi.org/10.7763/IJCCE.2013.V2.148
[17] Wang, Z. T., Zhao, N. B., Wang, W. Y., Tang, R., & Li, S. Y. (2015). A fault diagnosis approach for gas turbine exhaust gas temperature based on fuzzy c-means clustering and support vector machine. Mathematical Problems in Engineering, 2015. http://dx.doi.org/10.1155/2015/240267
[18] Gary, A. C., Wakefield, M. I., Johnson, G. W., & Ekart, D. D. (2009). Application of fuzzy c-means clustering to paleoenvironmental analysis: example from the Jurassic, central North Sea, UK. Geologic Problem Solving with Microfossils: A Volume in Honor of Garry D. Jones. SEPM Special Publication, 93, 9-20. http://dx.doi.org/10.2110/sepmsp.093.009
[19] Bezdek, J. C., Ehrlich, R., & Full, W. (1984). FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences, 10(2-3), 191-203. https://doi.org/10.1016/0098-3004(84)90020-7
[20] Carpenter, G. A., & Grossberg, S. (Eds.). (1991). Pattern recognition by self-organizing neural networks. MIT Press.
[21] Kohonen, T. (1998). The self-organizing map. Neurocomputing, 21(1-3), 1-6. http://dx.doi.org/10.1016/S0925-2312(98)00030-7
[22] Kohonen, T. (1990). The self-organizing map. Proceedings of the IEEE, 78(9), 1464-1480. https://doi.org/10.1109/5.58325
[23] Kohonen, T., Hynninen, J., Kangas, J., & Laaksonen, J. (1996). Som pak: The self-organizing map program package. Report A31, Helsinki University of Technology, Laboratory of Computer and Information Science.
[24] Anifah, L., Purnama, I. K. E., Hariadi, M., & Purnomo, M. H. (2013). Osteoarthritis classification using self-organizing map based on gabor kernel and contrast-limited adaptive histogram equalization. The open biomedical engineering journal, 7, 18. http://dx.doi.org/10.2174/1874120701307010018
[25] Oliver, M. A., & Webster, R. (1990). Kriging: a method of interpolation for geographical information systems. International Journal of Geographical Information System, 4(3), 313-332. http://dx.doi.org/10.1080/02693799008941549
[26] Adhikary, P. P., Dash, C. J., Bej, R., & Chandrasekharan, H. (2011). Indicator and probability kriging methods for delineating Cu, Fe, and Mn contamination in groundwater of Najafgarh Block, Delhi, India. Environmental monitoring and assessment, 176(1-4), 663-676. https://doi.org/10.1007/s10661-010-1611-4
[27] Cheng, Q. (1999). Spatial and scaling modelling for geochemical anomaly separation. Journal of Geochemical exploration, 65(3), 175-194. https://doi.org/10.1016/S0375-6742(99)00028-X


@article{Shirazi07041001,
title = " Exploration Geochemistry Data-Application for Cu Anomaly Separation Based On Classical and Modern Statistical Methods in South Khorasan, Iran ",
journal = "International Journal of Science and Engineering Applications (IJSEA)",
volume = "7",
number = "4",
pages = "039 - 044 ",
year = "2018",
author = " Aref Shirazi, Ardeshir Hezarkhani , Adel Shirazy ",
}