Scientific Quarterly Journal of Geosciences

Scientific Quarterly Journal of Geosciences

The use of the Gray Wolf Optimizer algorithm in separating anomalies from the background, Case study: Alut area

Document Type : Original Research Paper

Authors
Kamran Mostafaei 1
Mohammadnabi Kianpour 2
Mahyar Yousefi 3
1 Department of Mining Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran
2 Faculty of Mining Engineering, Amirkabir University of Technology, Tehran, Iran
3 Faculty of Engineering, University of Malayer, Malayer, Iran
10.22071/gsj.2023.401546.2094
Abstract
This article is devoted to introducing a novel application of the Gray Wolf Optimizer (GWO) algorithm in one of the most challenging issues related to mineral exploration, anomaly separation from the background in stream sediment geochemical studies. The Alut geological sheet, located in the Sanandaj-Sirjan zone, which has special importance to gold prospecting, has been studied for the distribution of gold and arsenic that accompany each other as the paracenteses in such deposits. The cost function used in this algorithm has been provided according to previously well-explored deposits. While the GWO algorithm was able to divide the sheet into two classes of anomalous and non-anomalous areas, the fractal method identified four categories among distributions of gold and arsenic, which impose the responsibility of selecting anomalous areas on the scientists. The GWO draws the areas as potential zones of prospecting that may be neglected by fractal strategy. The derived results show that 24.8ppm and 15.7ppb is anomaly threshold for arsenic and gold distribution respectively. The comparison of the results shows that the anomaly threshold obtained by the fractal methods and GWO algorithm for arsenic is almost the same, but the anomaly threshold for gold in the GWO algorithm method is optimal.
Keywords
Optimization Algorithm
Gray Wolf
Anomaly Separation
Gold
Alut

Subjects

Afzal, P., Ahari, H. D., Omran, N. R., and Aliyari, F., 2013. Delineation of gold mineralized zones using concentration–volume fractal model in Qolqoleh gold deposit, NW Iran. Ore Geology Reviews, 55, 125-133. https://doi.org/10.1016/j.oregeorev.2013.05.005
Afzal, P., Fadakar, Y., Khakzad, A., Moarefvand, P., Rashidnezhad Omran, N.A., and Asadi Harouni, H., 2010. Separation of Geochemical Anomalies from Background by Using of Power Spectral-Area Fractal Method, Case Study: Kahang Porphyry Cu-Mo Deposit, Isfahan. Journal of Earth and Resources, 2(2 (5)), 9-20 [in Persian].
Afzal, P., Mirzaei, M., Yousefi, M., Adib, A., Khalajmasoumi, M., Zarifi, A. Z., and Yasrebi, A. B., 2016. Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis. Journal of African Earth Sciences, 119, 139-149. https://doi.org/10.1016/j.jafrearsci.2016.03.009
Ahmadi, F., Mohamadpour, M., 2018. Geochemical studies of stream sediment to determine the shear zone-related gold mineralization (Case study of Alut area in Kurdistan province), Iranian Journal of Environmental Geology, 12(44), 19-35 [in Persian].
Ahmed, Q. I., Attar, H., Amer, A., Deif, M. A., and Solyman, A. A., 2023. Development of a Hybrid Support Vector Machine with Grey Wolf Optimization Algorithm for Detection of the Solar Power Plants Anomalies. Systems, 11(5), 237. https://doi.org/10.3390/systems11050237.
Aliyari, F., Rastad, E., and Arehart, G. B., 2009. Geology and geochemistry of D-O-C isotope systematics of the Qolqoleh Gold Deposit, Northwestern Iran: implications for ore genesis. Ore Geol. Rev., 36, 306–314. https://doi.org/10.1016/j.oregeorev.2009.06.003.
Aliyari, F., Rastad, E., and Mohajjel, M., 2012. Gold Deposits in the Sanandaj–Sirjan Zone: Orogenic Gold Deposits or Intrusion‐Related Gold Systems?" Resource Geology 62.3: 296-315. https://doi.org/10.1111/j.1751-3928.2012.00196.x.
Almazini, H. F., Ku-Mahamud, K. R., and Almazini, H., 2023. Heuristic Initialization Using Grey Wolf Optimizer Algorithm for Feature Selection in Intrusion Detection. Int. J. Intell. Eng. Syst, 16(1), 410-418. DOI: 10.22266/ijies2023.0228.36
Aryafar, A., Khosravi, V., Farshadmehr, M. A., and Yousefi, S., 2020. Using hybrid factor-fractal model for identification of Au, As, Sb mineral potential in Basiran 1:100000 sheet, south Khorasan, and east of Iran. Researches in Earth Sciences, 11(2), 127-142. doi: 10.52547/esrj.11.2.127 [in Persian].
Chen, Y., and Lu, L., 2023. The Anomaly Detector, Semi-supervised Classifier, and Supervised Classifier Based on K-Nearest Neighbors in Geochemical Anomaly Detection: A Comparative Study. Mathematical Geosciences, 1-23. https://doi.org/10.1007/s11004-022-10042-w .
Chen, Y., and Shayilan, A., 2022. Dictionary learning for multivariate geochemical anomaly detection for mineral exploration targeting. Journal of Geochemical exploration, 235, 106958. https://doi.org/10.1016/j.gexplo.2022.106958
Chen, Y., Lu, L., and Li, X., 2014. Application of continuous restricted Boltzmann machine to identify multivariate geochemical anomaly. Journal of Geochemical Exploration, 140, 56-63. https://doi.org/10.1016/j.gexplo.2014.02.013.
Chen, Z., Xiong, Y., Yin, B., Sun, S., and Zuo, R., 2023. Recognizing geochemical patterns related to mineralization using a self-organizing map. Applied Geochemistry, 151, 105621. https://doi.org/10.1016/j.apgeochem.2023.105621.
Cheng, Q., and Li, Q., 2002. A fractal concentration–area method for assigning a color palette for image representation. Computers & geosciences, 28(4), 567-575. https://doi.org/10.1016/S0098-3004(01)00060-7
Cui, Z. H., and GAO, X. Z., 2012. Theory and applications of swarm intelligence. J. Neural Computing and Applications. 21, 205–206. https://doi.org/10.1007/s00521-011-0523-8.
Darvishzadeh, A., 2015. Geology of Iran, Amirkabir Publication, 6th Edition, 434pp [in Persian].
Derrac, J., García, S., and Molina, D., 2011. A practical tutorial on the use of non-parametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. J. Swarm and Evolutionary Computation. 1, 3–18. https://doi.org/10.1016/j.swevo.2011.02.002 .
Eftkharnejad, J., 1972. Geological map of Mahabad, scale 1:250000, Geology Survey and Mineral Exploration of Iran [in Persian].
Farhadi, S., Afzal, P., Boveiri Konari, M., Daneshvar Saein, L., and Sadeghi, B., 2022. Combination of Machine Learning Algorithms with Concentration-Area Fractal Method for Soil Geochemical Anomaly Detection in Sediment-Hosted Irankuh Pb-Zn Deposit, Central Iran. Minerals, 12(6), 689. https://doi.org/10.3390/min12060689.
Haji Aliaskari, A., Maghsoudi, A., Javandel, P., and Ghezelbash, R., 2018. Identification of geochemical popualations using PCA and U-spatial statistics model in Shamkan 100000 sheet, 10th conference of economic geology of Iran, Esfahan [in Persian].
Hassani Pak., A.A., 2015. Geochemical Exploration, University of Tehran Publication, 615pp [in Persian].
Hassani Pak., A.A., and Sharafodin, M., 2011. Exploration Data Analyses, University of Tehran Publication, 1010pp [in Persian].
Hassani Pak., A.A. 2000, Report of systematic geochemical exploration in the area of Alut, Kurdistan Industrials and Mining organization [in Persian].
Hendi, R., 2003. Report of geochemical exploration in the area of Alut, Geology Survey and Mineral Exploration of Iran [in Persian].
Hendi, R., 2004. Report of litho-geochemical exploration in the area of Alut, Geology Survey and Mineral Exploration of Iran [in Persian].
Hosseini, S.A., Shahrokhi, S.V., Afzal, P., Farhadinejad, T., and Imanzadeh, H., 2017. Separation of Geochemical Anomalies Using Concentration- Area and Concentration- Number Methods in the Alut 1:100,000 Sheet, Kurdistan. Geosciences, 27(105), 199-206 [in Persian].
Kananian, A., Jafari, M., and Nazzari, A., 2018. Discrimination of Pb and Zn geochemical anomalies using classical, multifractal (C-N) and (C-A) and singularity index statistical methods in Arak 1:100000 sheet, Journal of Advanced Applied Geology, 8(29), 63-74, doi: 10.22055/aag.2019.26910.1887. [in Persian].
Khezri, A., Mohammadzadeh, M.J., and Nouri, A., 2013. Comparison of neural network and PCANN methods in order to identify gold mineralization in Alut Area, Kurdistan, 5th conference of economic geology of Iran, Ferdowsi university of Mashhad [in Persian].
Leboucher, C., Chelouah, R., Siarry, P., and Le Ménec, S., 2012. A swarm intelligence method combined to evolutionary game theory applied to the resources allocation problem. International Journal of Swarm Intelligence Research (IJSIR), 3(2), 20-38. DOI: 10.4018/jsir.2012040102
Li, S. Y., Wang, S. M., Wang, P. F., Su, X. L., Zhang, X. S., and Dong, Z. H., 2018. An improved grey wolf optimizer algorithm for the inversion of geoelectrical data. Acta Geophysica, 66(4), 607-621. https://doi.org/10.1007/s11600-018-0148-8.
Li, S., Mao, J., and Li, Z. 2023. An EEMD-SVD method based on gray wolf optimization algorithm for lidar signal noise reduction. International Journal of Remote Sensing, 44(17), 5448-5472. https://doi.org/10.1080/01431161.2023.2249597 .
Luo, Z., Zuo, R., Xiong, Y., and Zhou, B. 2023. Metallogenic-Factor Variational Autoencoder for Geochemical Anomaly Detection by Ad-Hoc and Post-Hoc Interpretability Algorithms. Natural Resources Research, 1-19. https://doi.org/10.1007/s11053-023-10200-9.
Maghsoudi, A., Rashidi, B., and Rahmani, M., 2004.  Deposits and mine index of gold in Iran, Arian Zamin publication, 388pp [in Persian].
Mahdiyanfar, H., and Seyedrahimi-Niaraq, M., 2022. Improvement of geochemical prospectivity mapping using power spectrum–area fractal modeling of multi-element mineralization factor (SAF-MF). Geochemistry: Exploration, Environment, Analysis (2022): geochem2022-015. https://doi.org/10.1144/geochem2022-015.
Mirjalili, S.A., Mirjalili, S.M., and Lewis, A., 2014. Grey wolf optimizer. Advances in engineering software 69: 46-61. https://doi.org/10.1016/j.advengsoft.2013.12.007.
Misaghi, F., Amani, A. H., and Seddigh, A. R., 2020. Comparison of the efficiency of gray wolf optimizer and imperialist competitive algorithms in an optimal allocation of water in irrigation and drainage networks (case study: Sofi-Chay network). Environmental Sciences, 18(2), 203-218. doi: 10.29252/envs.18.2.203 [in Persian].
Mohammadi, N. M., Hezarkhani, A., and Saljooghi, B. S., 2016. Separation of a geochemical anomaly from background by fractal and U-statistic methods, a case study: Khooni district, Central Iran. Geochemistry, 76(4), 491-499. https://doi.org/10.1016/j.chemer.2016.09.001.
Mohammadpour, M., Abedi, M., Rahimopor, Gh., Jozanikohan, G., and Khalifiani, F., 2019. Geochemical distribution mapping by combining number-size multifractal model and multiple indicator kriging, Journal of Geochemical Exploration, 200, 13-26. https://doi.org/10.1016/j.gexplo.2019.01.018.
Mohammadpour, M., Rahimipour, Gh., and Ghzanfari, M., 2012. Geochemical investigation of stream sediments to determination of paragenetic features of shear zone gold mineralization in Alut, 16th conference of the geological society of Iran [in Persian].
Mostafaei, K., and Kianpour, M., 2022. Application of Magnetometry in Manto-type Copper Deposit Exploration, Case study: Meyami, Iran. Rudarsko-geološko-Naftni Zbornik, 37(5), 1–14. https://doi.org/10.17794/rgn.2022.5.1.
Mostafaei, K., and Ramazi, H., 2018. Compiling and verifying 3D models of 2D induced polarization and resistivity data by geostatistical methods. Acta Geophysica, 66, 959-971. https://doi.org/10.1007/s11600-018-0175-5.
Mostafaei, K., and Ramazi, H., 2019. Mineral resource estimation using a combination of drilling and IP-Rs data using statistical and cokriging methods. Bulletin of the mineral research and exploration, 160(160), 177-195. https://doi.org/10.19111/bulletinofmre.502794.
Mostafaei, K., Maleki, S., Jodeiri Shokri, B., and Yousefi, M., 2023a. Predicting gold grade by using support vector machine and neural network to generate an evidence layer for 3D prospectivity analysis. International Journal of Mining and Geo-Engineering. doi: 10.22059/ijmge.2023.362951.595087.
Mostafaei, K., Kianpour, M., and Yousefi, M., 2023b. Delineation of gold exploration targets based on the prospectivity models through an optimization algorithm. Journal of Mining and Environment. doi: 10.22044/jme.2023.13472.2489.
Nadimi-Shahraki, M. H., Taghian, S., and Mirjalili, S., 2021. An improved grey wolf optimizer for solving engineering problems. Expert Systems with Applications, 166, 113917.  https://doi.org/10.1016/j.eswa.2020.113917.
Omrani, J., and Khabaznia, A, R., 2003. Geological map of Alut, Scale: 1000000, Geological survey and mineral Exploration of Iran [in Persian].
Otair, M., Ibrahim, O. T., Abualigah, L., Altalhi, M., and Sumari, P., 2022. An enhanced grey wolf optimizer-based particle swarm optimizer for intrusion detection system in wireless sensor networks. Wireless Networks, 28(2), 721-744. https://doi.org/10.1007/s11276-021-02866-x.
Parpinelli, R. S., and Lopes, H. S., 2011. New inspirations in swarm intelligence: a survey. J. International Journal of Bio-Inspired Computation. 3, 1–16. https://doi.org/10.1504/IJBIC.2011.0387.
Rahimi, M.R., Moradzadeh, A., Abedi, M., and Arabamiri, A., 2016. Use the fractal analysis for gold exploration in Alut area, national conference of research in earth sciences [in Persian].
Reimann, C., Filzmoser, P., Hron, K., Kynčlová, P., and Garrett, R. G., 2017. A new method for correlation analysis of compositional (environmental) data–a worked example. Science of the Total Environment, 607, 965-971. https://doi.org/10.1016/j.scitotenv.2017.06.063.
Sepahi, A. A., Ghoreishvandi, H., Maanijou, M., Maruoka, T., and Vahidpour, H., 2020. Geochemical description and sulfur isotope data for Shahrak intrusive body and related Fe‐mineralization (east Takab), northwest Iran. Island Arc, 29(1), e12367. https://doi.org/10.1111/iar.12367
Seyedrahimi-Niaraq, M., and Hekmatnejad, A., 2021. The efficiency and accuracy of probability diagram, spatial statistic and fractal methods in the identification of shear zone gold mineralization: a case study of the Saqqez gold ore district, NW Iran. Acta Geochimica, 40, 78-88. https://doi.org/10.1007/s11631-020-00413-7.
Seyedrahimi-Niaraq, M., Mahdiyanfar, H., and Mokhtari, A. R., 2023. Application of geochemical structural methods to determine lead-contaminated areas related to mining activities. Journal of Analytical and Numerical Methods in Mining Engineering, 13(34), 41-55. doi: 10.22034/anm.2022.2783[in Persian].
Zhang, Z., Long, K., Wang, J., and Dressler, F., 2013. On swarm intelligence inspired self-organized networking: its bionic mechanisms, designing principles and optimization approaches. IEEE Communications Surveys & Tutorials, 16(1), 513-537. https://doi.org/10.1109/SURV.2013.062613.00014.
Scientific Quarterly Journal of Geosciences
Volume 34, Issue 2 - Serial Number 132
Summer 2024, Vol. 34, Issue 2, Serial No. 132
Spring 2024
Pages 75-88