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Application of stepwise weight assessment ratio analysis (SWARA) for copper prospectivity mapping in the Anarak region, central Iran

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Abstract

Nowadays, using Multi-Criteria Decision-Making (MCDM) techniques are common in all fields of study because of their advantage for finding optimal results. Some of the MCDM techniques like analytic network process (ANP), factor relationship (FARE), and analytic hierarchy process (AHP) are so popular in mining exploration due to the obtaining of geochemical anomalies and mineral prospectivity maps. The aim of this study is to utilize the stepwise weight assessment ratio analysis (SWARA) method for prospecting copper in the Anarak region, central Iran. The SWARA method is a developed MCDM knowledge-based technique in accordance with ratio of the different criteria. Informative layers include geological, geochemical, geophysical, and remote sensing data and have been integrated in this study. The data was classified according to the relation of copper occurrences/deposits in the Anarak region by the geographical information system (GIS). Following that, the every classified sub-criteria was weighted by the SWARA method and the weighted classified factors for determination of copper prospects were overlapped. Subsequently, the gained results illustrated the main copper prospects in the NW and NE parts of the region. Furthermore, the prospectivity map has a meaningful correlation with copper occurrences/deposits in the Anarak region. As a result, using the operating receiver characteristics (ORC) technique validates copper prospects derived via the SWARA method in the study region as high as 70% and validation result shows that the area under curve (ROC) is 0.79. Results derived via the SWARA were compared with the AHP method and the SWARA method is validated especially in NW part.

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References

  • Abedi M, Norouzi G-H (2012) Integration of various geophysical data with geological and geochemical data to determine additional drilling for copper exploration. J Appl Geophys 83:35–45

    Article  Google Scholar 

  • Abedi M, Norouzi G-H (2016) A general framework of TOPSIS method for integration of airborne geophysics, satellite imagery geochemical and geological data. Int J Appl Earth Obs Geoinf 46:31–44

    Article  Google Scholar 

  • Abedi M, Norouzi G-H, Bahroudi A (2012) Support vector machine for multi-classification of mineral prospectivity areas. Comput Geosci 46:272–283

    Article  Google Scholar 

  • Abedi M, Norouzi G-H, Fathianpour N (2013) Fuzzy outranking approach: a knowledge-driven method for mineral prospectivity mapping. Int J Appl Earth Obs Geoinf 21:556–567

    Article  Google Scholar 

  • Afzal P, Khakzad A, Moarefvand P, Omran NR, Esfandiari B, Alghalandis YF (2010) Geochemical anomaly separation by multifractal modeling in Kahang (Gor Gor) porphyry system. Central Iran: J Geochem Explor 104(1–2):34–46

    Google Scholar 

  • Afzal P, Fadakar Alghalandis Y, Khakzad A, Moarefvand P, Rashidnejad Omran N (2011) Delineation of mineralization zones in porphyry Cudeposits by fractal concentration–volume modeling. J Geochem Explor 108:220–232

    Article  Google Scholar 

  • Agterberg FP, Bonham-Carter GF (1999) Logistic regression and weights of evidence modeling in mineral exploration. In: proc. 28th Int. Symp App Comput Mineral Ind (APCOM)

  • Agterberg FP, Bonham-Carter GF, Wright DF (1990) Statistical pattern integration for mineral exploration* A2 - GAÁL, GABOR. In: Merriam DF (ed) Computer applications in resource estimation. Pergamon, Amsterdam, pp 1–21

    Google Scholar 

  • Albayrak E, Erensal YC (2004) Using analytic hierarchy process (AHP) to improve human performance. An application of multiple criteriadecision making problem. J Intell Manuf 15:491–503

    Article  Google Scholar 

  • Almeida-Dias J, Figueira JR, Roy B (2010) Electre Tri-C: a multiple criteria sorting method based on characteristic reference actions. Eur J Oper Res 204(3):565–580

    Article  Google Scholar 

  • Bagheri H (2015) Crustal lineament control on mineralization in the Anarak area of Central Iran. Ore Geol Rev 66:293–308

    Article  Google Scholar 

  • Bagheri H, Moore F, Alderton DHM (2007) Cu–Ni–Co–As (U) mineralization in the Anarak area of central Iran. J Asian Earth Sci 29(5–6):651–665

    Article  Google Scholar 

  • Bitarafan M, Hashemkhani Zolfani S, Arefi SL, Zavadskas EK (2012) Evaluating the construction methods of cold-formed steel structures in reconstructing the areas damaged in natural crises, using the methods AHP and COPRAS-G. Arch Civ Mech Eng 12(3):360–367

    Article  Google Scholar 

  • Bous G, Fortemps P, Glineur F, Pirlot M (2010) ACUTA: a novel method for eliciting additive value functions on the basis of holistic preference statements. Eur J Oper Res 206(2):435–444

    Article  Google Scholar 

  • Brauers WKM, Zavadskas EK, Peldschus F, Turskis Z (2008) Multi objective optimization of road design alternatives with an application of the MOORA method: proceedings of the 25 th International Symposium on Automation and Robotics in Construction. Vilnius Gediminas Technical University, Lithuania

    Google Scholar 

  • Buchs DM, Bagheri S, Martin L, Hermann J, Arculus R (2013) Paleozoic to Triassic ocean opening and closure preserved in Central Iran: constraints from the geochemistry of meta-igneous rocks of the Anarak area. Lithos 172–173:267–287

    Article  Google Scholar 

  • Caranza EJM, Hale M (2001) Logistic regression for geologically constrained mapping of gold potential, Baguio District, Philippines. Nat Resour Res 10(2):125–136

    Article  Google Scholar 

  • Caranza EJM, Hale M (2002) Where are porphyry copper deposits spatially localized? A case study in Benguet Province, Philippines. Nat Resour Res 11(1):45–59

    Article  Google Scholar 

  • Carranza EJM (2008) Geochemical anomaly and mineral prospectivity mapping in GIS p 368

  • Carranza EJM (2009) Handbook of exploration and environmental geochemistry, Chapter 7: knowledge-driven modeling of mineral prospectivity, vol 11, Elsevier, Amsterdam

  • Carranza EJM, Hale M (2003) Evidential belief functions for data-driven geologically constrained mapping of gold potential, Baguio district Philippines. Ore Geol Rev 22(1–2):117–132

    Article  Google Scholar 

  • Carranza EJM, Laborte AG (2015) Random forest predictive modeling of mineral prospectivity with small number of prospects and data with missing values in Abra (Philippines). Comput Geosci 74:60–70

    Article  Google Scholar 

  • Carranza EJM, Mangaoang JC, Hale M (1999) Application of mineral exploration models and GIS to generate mineral potential maps as input for optimum land-use planning in the Philippines. Nat Resour Res 8(2):165–173

    Article  Google Scholar 

  • Carranza EJM, Woldai T, Chikambwe EM (2005) Application of data-driven evidential belief functions to prospectivity mapping for aquamarine-bearing Pegmatites, Lundazi District, Zambia. Nat Resour Res 14(1):47–63

    Article  Google Scholar 

  • Carranza EJM, van Ruitenbeek FJA, Hecker C, van der Meijde M, van der Meer FD (2008a) Knowledge-guided data-driven evidential belief modeling of mineral prospectivity in Cabo de Gata SE Spain. Int J Appl Earth Obs Geoinf 10(3):374–387

    Article  Google Scholar 

  • Carranza EJM, Wibowo H, Barritt SD, Sumintadireja P (2008b) Spatial data analysis and integration for regional-scale geothermal potential mapping, West Java, Indonesia. Geothermics 37(3):267–299

    Article  Google Scholar 

  • Cheng Q, Agterberg FP (1999) Fuzzy weights of evidence and its application in mineral potential mapping. Nat Resour Res 8(1):27–35

  • Cheng Q, Agterberg FP, Ballantyne SB (1994) The separation of geochemical anomalies from background by fractal methods. J Geochem Explor 51:109–130

    Article  Google Scholar 

  • Churchman CW, Ackoff RL (1954) An approximate measure of value. J Oper Res Soc Am 2(2):172–187

    Google Scholar 

  • Dagdeviren M, Yavuz S, Kilinc N (2009) Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Syst Appl 36(4):8143–8151

    Article  Google Scholar 

  • Deng J, Wang Q, Yang L, Wang Y, Gong Q, Liu H (2010) Delineation and explanation of geochemical anomalies using fractal models in the Heqing area, Yunnan Province, China. J Geochem Explor 105(3):95–105

    Article  Google Scholar 

  • Du Bois P, Brans JP, Cantraine F, Mareschal B (1989) MEDICIS: an expert system for computer-aided diagnosis using the PROMETHEE multicriteria method. Eur J Oper Res 39(3):284–292

    Article  Google Scholar 

  • Elshkaki A, Graedel TE, Ciacci L, Reck BK (2016) Copper demand, supply, and associated energy use to 2050. Glob Environ Chang 39:305–315

    Article  Google Scholar 

  • Farahbakhsh E, Shirmard H, Bahroudi A, Eslamkish T (2016) Fusing ASTER and QuickBird-2 satellite data for detailed investigation of porphyry copper deposits using PCA; case study of Naysian Deposit, Iran. J Indian Soc Remote Sens 44(4):525–537

    Article  Google Scholar 

  • Gabr S, Ghulam A, Kusky T (2010) Detecting areas of high-potential gold mineralization using ASTER data. Ore Geol Rev 38(1–2):59–69

    Article  Google Scholar 

  • Ginevičius R (2011) A new determining method for the criteria weights in multicriteria evaluation. Int J Inf Technol Decis Mak 10(6):1067–1095

    Article  Google Scholar 

  • Goodacre AK, Bonham-Carter GF, Agterberg FP, Wright DF (1993) A statistical analysis of the spatial association of seismicity with drainage patterns and magnetic anomalies in western Quebec. Tectonophysics 217(3–4):285–305

    Article  Google Scholar 

  • Grigoroudis E, Siskos Y (2002) Preference disaggregation for measuring and analysing customer satisfaction: the MUSA method. Eur J Oper Res 143(1):148–170

    Article  Google Scholar 

  • Hale M, Carranza EJM (2002) Wildcat mapping of gold potential, Baguio District, Philippines. Appl Earth Sci Trans Inst Min Metall Sect B 111(2):100–105

    Article  Google Scholar 

  • Harris D, Zurcher L, Stanley M, Marlow J, Pan G (2003) A comparative analysis of favorability mappings by weights of evidence, probabilistic neural networks, discriminant analysis, and logistic regression. Nat Resour Res 12(4):241–255

    Article  Google Scholar 

  • Hashemkhani Zolfani S, Bahrami M (2014) Investment prioritizing in high tech industries based on SWARA-COPRAS approach. Technol Econ Dev Econ 20(3):534–553

    Article  Google Scholar 

  • Hosseini SA, Abedi M (2015) Data envelopment analysis: a knowledge-driven method for mineral prospectivity mapping. Comput Geosci 82:111–119

    Article  Google Scholar 

  • Hwang CL, Yoon K (1981) Multiple attribute decision making. Springer-Verlag, Berlin Heidelberg

    Book  Google Scholar 

  • Jacquet-Lagreze E, Siskos J (1982) Assessing a set of additive utility functions for multicriteria decision-making, the UTA method. Eur J Oper Res 10(2):151–164

    Article  Google Scholar 

  • Johnson RA, Wichern DW (2002) Applied multivariate statistical analysis, 5th edn. Rentice Hall, New Jersey

    Google Scholar 

  • Jolliffe IT (2002) Principal component analysis, 2nd edn. Springer, Berlin, pp 1–487

    Google Scholar 

  • Jung D, Kursten M (1976) Post Mesozoic volcanism in Iran and its relation to the subduction of the Afro–Arabian under the Eurasian plate. In: Afar—between continental and oceanic rifting, Bad Bergzabern, Inter - union Comm Geodyn Sci Rep

  • Kaklauskas A, Zavadskas EK, Raslanas S, Ginevicius R, Komka A, Malinauskas P (2006) Selection of low-e windows in retrofit of public buildings by applying multiple criteria method COPRAS: a Lithuanian case. Energ Buildings 38(5):454–462

    Article  Google Scholar 

  • Katz EM (1982) Lineament analysis of landsat imagery applied to mineral exploration. In: Laming DJC, Gibbs AK (eds), Hidden wealth: mineral exploration techniques in tropical forest areas: Geosciences in International Devolopment, v. AGID Report No.7, p 157–166

  • Keršulienė V, Turskis Z (2011) Integrated fuzzy multiple criteria decision making model for architect selection. Technol Econ Dev Econ 17(4):645–666

    Article  Google Scholar 

  • Keršuliene V, Zavadskas EK, Turskis Z (2010) Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (Swara). J Bus Econ Manag 11(2):243–258

    Article  Google Scholar 

  • Li CJ, Ma TH, Shi JF (2003) Application of a fractal method relating concentration and distances for separation of geochemical anomalie from background. J Geochem Explor 77:167–175

    Article  Google Scholar 

  • Ma T, Li C, Lu Z (2014) Estimating the average concentration of minor and trace elements in surficial sediments using fractal methods. J Geochem Explor 139:207–216

    Article  Google Scholar 

  • Mandelbrot BB (1983) The fractal geometry of nature. WH Freeman, San Francisco, pp 1–468

    Google Scholar 

  • Marjoribanks R (2010) Geological methods in mineral Exploration and mining. Springer, Heidelberg

    Book  Google Scholar 

  • Mejía-Herrera P, Royer J-J, Caumon G, Cheilletz A (2015) Curvature attribute from surface-restoration as predictor variable in Kupferschiefer Copper Potentials. Nat Resour Res 24(3):275–290

    Article  Google Scholar 

  • Mulliner E, Smallbone K, Maliene V (2013) An assessment of sustainable housing affordability using a multiple criteria decision making method. Omega 41(2):270–279

    Article  Google Scholar 

  • Nykänen V (2008) Radial basis functional link nets used as a prospectivity mapping tool for orogenic gold deposits within the Central Lapland Greenstone Belt, Northern Fennoscandian Shield. Nat Resour Res 17(1):29–48

    Article  Google Scholar 

  • Opricovic S, Tzeng G-H (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156(2):445–455

    Article  Google Scholar 

  • Ovchinnikov LN (1971) Prognostic evaluation of world reserves of metals in land deposits, p 638-686

  • Pan G, Harris DP (2000) Information synthesis for mineral exploration, p 461

  • Pazand K, Hezarkhani A, Ataei M, Ghanbari Y (2011) Application of multifractal modeling technique in systematic geochemical stream sediment survey to identify copper anomalies: a case study from Ahar, Azarbaijan, Northwest Iran. Chem Erde-Geochem 71(4):397–402

    Article  Google Scholar 

  • Porwal A, Carranza EJM, Hale M (2004) A hybrid neuro-fuzzy model for mineral potential mapping. Math Geol 36(7):803–826

  • Porwal A, Carranza EJM, Hale M (2006) Bayesian network classifiers for mineral potential mapping. Comput Geosci 32(1):1–16

    Article  Google Scholar 

  • Ramezani J, Tucker R (2003) The Saghand region, Central Iran: U-Pb geochronology, petrogenesis and implication for Gondwana tectonics. Am J Sci 303:622–665

    Article  Google Scholar 

  • Roubens M (1982) Preference relations on actions and criteria in multicriteria decision making. Eur J Oper Res 10(1):51–55

    Article  Google Scholar 

  • Saaty TL, Vargas LG (1979) Estimating technological coefficients by the analytic hierarchy process. Socio Econ Plan Sci 13(6):333–336

    Article  Google Scholar 

  • Saaty TL, Vargas LG (2001) Models, methods, concepts & applications of the Analytic Hierarchy Process, vol 34. International Series in Operations Research & Management Science. Springer, Berlin

    Book  Google Scholar 

  • Sabins FF (1999) Remote sensing for mineral exploration. Ore Geol Rev 14(3–4):157–183

    Article  Google Scholar 

  • Sadeghi B, Moarefvand P, Afzal P, Yasrebi AB, Daneshvar Saein L (2012) Application of fractal models to outline mineralized zones in the Zaghia iron ore deposit, Central Iran. J Geochem Explor 122:9–19

    Article  Google Scholar 

  • Sahandi MR, Delavar ST, Sadeghi M, Jafari A, Moosavi A (2005) Geological map of Iran (1:1,000,000). Geological Survey of Iran. <http://www.ngdir.ir>

  • Sánchez-Lozano JM, Teruel-Solano J, Soto-Elvira PL, Socorro García-Cascales M (2013) Geographical information systems (GIS) and multi-criteria decision making (MCDM) methods for the evaluation of solar farms locations: case study in south-eastern Spain. Renew Sust Energ Rev 24:544–556

    Article  Google Scholar 

  • Shahriari H, Ranjbar H, Honarmand M (2013) Image segmentation for hydrothermal alteration mapping using PCA and concentration–area fractal model. Nat Resour Res 22:191–206

    Article  Google Scholar 

  • Stanujkic D, Karabasevic D, Zavadskas EK (2015) A Framework for the Selection of a Packaging Design Based on the SWARA Method; Inzinerine Ekonomika-Engineering Economics 26(2):181–187

  • Tarkian M, Bock WD, Neumann M (1983) Geology and mineralogy of the Cu−Ni−Co−U ore deposits at Talmessi and Meeskani, central Iran. Tschermaks Mineral und Petrogr Mitt 32(2):111–133

    Article  Google Scholar 

  • Vural A, Corumluoglu O, Asri I (2016) Exploring Gördes zeolite sites by feature oriented principle component analysis of LANDSAT images. Caspian J Environ Sci 14(4):285–298

    Google Scholar 

  • Wellman HW (1966) Active wrench faults of Iran, Afghanistan and Pakistan. Geol Rundsch 55(3):716–735

    Article  Google Scholar 

  • Yousefi M, Carranza EJM (2015) Geometric average of spatial evidence data layers: a GIS-based multi-criteria decision-making approach to mineral prospectivity mapping. Comput Geosci 83:72–79

    Article  Google Scholar 

  • Yousefi M, Carranza EJM (2016) Data-driven index overlay and Boolean logic mineral prospectivity modeling in Greenfield exploration. Nat Resour Res 25:3–18

  • Yousefi M, Nykanen V (2016) Data-driven logistic-based weighting of geochemical and geological evidence layers in mineral prospectivity mapping. J Geochem Explor 164:94–106

    Article  Google Scholar 

  • Yousefi M, Nykanen V (2017) Introduction to the special issue: GIS-based mineral potential targeting. J Afr Earth Sci 128:1–4

    Article  Google Scholar 

  • Yousefi M, Kamkar-Rouhani A, Carranza EJM (2012) Geochemical mineralization probability index (GMPI): a new approach to generate enhanced stream sediment geochemical evidential map for increasing probability of success in mineral potential mapping. J Geochem Explor 115:24–35

    Article  Google Scholar 

  • Zaidi FK, Nazzal Y, Ahmed I, Naeem M, Jafri MK (2015) Identification of potential artificial groundwater recharge zones in northwestern Saudi Arabia using GIS and Boolean logic. J Afr Earth Sci 111:156–169

    Article  Google Scholar 

  • Zavadskas EK, Turskis Z (2010) A new additive ratio assessment (ARAS) method in multicriteria decision-making. Ukio Technologinis ir Ekonominis Vystymas 16(2):159–172

    Google Scholar 

  • Zavadskas EK, Vainiunas P, Turskis Z, Tamosaitiene J (2012) Multiple criteria decision support system for assessment of projects managers in construction. Int J Inf Technol Decis Mak 11(02):501–520

    Article  Google Scholar 

  • Zhang Y, Robinson J, Schaubs PM (2011) Numerical modelling of structural controls on fluid flow and mineralization. Geosci Front 2(3):449–461

    Article  Google Scholar 

  • Zuo R, Carranza EJM (2011) Support vector machine: a tool for mapping mineral prospectivity. Comput Geosci 37(12):1967–1975

    Article  Google Scholar 

  • Zuo R, Wang J (2016) Fractal/multifractal modeling of geochemical data. J Geochem Explor 164:33–41

    Article  Google Scholar 

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Panahi, S., Khakzad, A. & Afzal, P. Application of stepwise weight assessment ratio analysis (SWARA) for copper prospectivity mapping in the Anarak region, central Iran. Arab J Geosci 10, 484 (2017). https://doi.org/10.1007/s12517-017-3290-8

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