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A new linguistic quantifier knowledge-guided OWA approach for mineral prospectivity mapping: a case study of the Bavanat Region, Iran

  • Reza Ghasemi
  • Behzad Tokhmechi
  • Gregor Borg
Original Paper

Abstract

The main purpose of this study is to introduce a geographic information system (GIS)-based, multi-criteria decision analysis method for selection of favourable environments for Besshi-type volcanic-hosted massive sulphide (VHMS) deposits. The approach integrates two multi-criteria decision methods (analytical hierarchy process and ordered weighted averaging) and theory of fuzzy sets, within a GIS environment, to solve the problem of big suggested areas and missing known ore deposits in favourable environment maps for time and cost reduction. We doubled the fuzzy linguistic variables’ significance as a method to apply the arrange weights that the analytical hierarchy process (AHP)-ordered weighted averaging (OWA) hybrid procedure depends on. Another aim of this work is to assist mineral deposit exploration by modelling existing uncertainty in decision-making. Both AHP and fuzzy logic methods are knowledge-based, and they are affected by decision maker judgments. We used data-driven OWA approach in a hybrid method for solving this problem. We applied a new knowledge-guided OWA approach on data with changing linguistic variables according to the mineral system for VHMS deposits. Additionally, we used a vector-based method combination, which increased the precision of results. Results of knowledge-guided OWA showed that all of the mines and discovered deposits have been predicted with 100% accuracy in half of the size of the suggested area. To summarize, results improved the selection of possible target sites and increased the accuracy of results as well as reducing the time and cost, which will be used for field exploration. Finally, the hybrid methods with a knowledge-guided OWA approach have delivered more reliable results compared to exclusively knowledge-driven or data-driven methods. The study proved that expert knowledge and processed data (information) are critical important keys to exploration, and both of them should be applied in hybrid methods for reaching reliable results in mineral prospectivity mapping.

Keywords

AHP-OWA Multi-criteria decision-making Fuzzy membership MPM VHMS Bavanat Region 

Notes

Acknowledgments

We would like to thank Mr. Fotovati and Dr. Sadeghi. We appreciate Prof. David Huston’s help with the conceptual model and criteria selection. Thanks to Jo Miles for providing English improvements and feedback. This manuscript was partly written during a study period at the Martin Luther University Halle-Wittenberg, Germany.

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Copyright information

© Saudi Society for Geosciences 2018

Authors and Affiliations

  1. 1.School of Mining, Petroleum and Geophysics EngineeringShahrood University of TechnologyShahroodIran
  2. 2.School of Mining, Petroleum and Geophysics EngineeringShahrood University of TechnologyShahroodIran
  3. 3.Institute for Geosciences and GeographyMartin Luther UniversityHalle-WittenbergGermany

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