Document Type : Review Paper
Authors
1 Mining and Petroleum Engineering Department, Faculty of Engineering, Al-Azhar University, Cairo, Egypt.
2 Nuclear Materials Authority, P.O. 530 El-Maadi, Cairo, Egypt
Abstract
This study aims to develop an empirical correlation model for estimating the uranium content of the G-V in the Gabal Gattar area, northeastern desert of Egypt, as a function of the thorium content and the total gamma rays. Using the recent MATLAB software, the effect of selecting tan-sigmoid as a transfer function at various numbers of hidden neurons was investigated to arrive at the optimum Artificial Neural Network (ANN) model. The pure-linear function was investigated as the output function, and the Levenberg-Marquardt approach was chosen as the optimization technique. Based on 1221 datasets, a novel ANN-based empirical correlation was developed to calculate the amounts of uranium (U). The results show a wide range of uranium content, with a determination coefficient (R2) of about 0.999, a Root Mean Square Error (RMSE) equal to 0.115%, a Mean Relative Error (MRE) of -0.05%, and a Mean Absolute Relative Error (MARE) of 0.76%. Comparing the obtained results with the field investigation shows that the suggested ANN model performed well.
Keywords
Main Subjects
[1]. Dragovic, S., Onjia, A., Stankovic, S., Anicin, I., and Bacic, G. (2005). Artificial neural network modelling of uncertainty in gamma-ray spectrometry. Nuclear Instruments and Methods in Physics Research, 540 (2-3), 455-463.
[2]. Al-Bulushi, N. I., Peter Robert King., Blunt, M. J., and Kraaijveld, M. (2012). Artificial neural networks workflow and its application in the petroleum industry. Neural Computing and Applications, 21, 409-421. doi 10.1007/s00521-010-0501-6
[3]. IAEA. (2007). Naturally occurring radioactive material. Proceedings of an International Symposium Held in Seville, Spain, pp.297-306.
[4]. UNSCEAR. (1988). Sources, effects and risks of ionizing radiation united nations scientific committee on the effects of atomic radiation 1988 report to the general assembly with annexes. United nations, New York, 647 P.
[5]. Sevim B., Mirac K., Ahmet B., and Fatih K. (2018). Forecasting of Ra-226, Th-232, and U-238 concentrations using artificial neural networks (anns). Cumhuriyet Science Journal,39-1, 87-94.
[6]. Rigo-J.P., Chica O. M., and Abarca F. (2003). Artificial neural networks as a tool for mineral potential mapping with GIS. International Journal of Remote Sensing, 24, 1151–1156.
[7]. Nezamolhosseini, S.A., Mojtahedzadeh, S.H., and Gholamnejad, J. (2017). The application of artificial neural networks to ore reserve estimation at Choghart Iron ore deposit. Analytical and Numerical Methods in Mining Engineering, 6, 73-83.
[8]. Bolandi, V., Kadkhodaie, A., and Farzi, R. (2017). Analyzing organic richness of source rocks from well log data by using SVM and ANN classifiers: A case study from the Kazhdumi formation, the Persian Gulf basin, offshore Iran. Journal of Petroleum Science and Engineering, 151, 224-234.
[9]. Ambrosino, F., Sabbarese, C., Roca, V., Giudicepietro, F., and Chiodini, G. (2020). Analysis of 7-years radon time series at Campi Flegrei area (Naples, Italy) using artificial neural network method. Applied Radiation Isotopes, 163, 109239. https://doi.org/10.1016/j.apradiso.2020.109239 [10]. Yasrebi, A.B., Hezarkhani, A., Afzal, P., Karami, R., Eskandarnejad Tehrani, M., and Borumandnia, A. (2020). Application of an ordinary kriging-artificial neural network for elemental distribution in kahang porphyry deposit, central Iran. Arabian Journal of Geosciences, 13(748), 1-14.
[11]. Afzal, P., Farhadi, S., ShamseddinMeigooni, M., BoveiriKonari, M., and Daneshvar Saein, L. (2022). Geochemical anomaly detection in the irankuh district using hybrid machine learning technique and fractal modeling. Geopersia, 12(1), 191-199. doi: 10.22059/GEOPE.2022.336072.648644
[12]. Farhadi, S., Afzal, P., BoveiriKonari, 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
[13]. Amit Kumar Gorai1, Simit Raval, Ashok Kumar Patel, Snehamoy Chatterjee, and Tarini Gautam. (2021). Design and development of a machine vision system using artificial neural network-based algorithm for automated coal characterization. International Journal of Coal Science &Technology, 8(4),737–755.
[14]. Sevim Bilici, Mirac Kamislioglu, Ahmet Bilici, and Fatih Kulahci. (2018). Forecasting of Ra-226, Th-232, and U-238 concentrations using artificial neural networks (ANNs). Cumhuriyet Science Journal, 39-1, 87-94.
[15]. Snezana Dragovic. (2022). Artificial neural network modeling in environmental radioactivity studies – A review. Science of the Total Environment, 847, 157526.
[16]. Cody A. Nizinski, Cuong Ly, Clement Vachet, Alex Hagen, TolgaTasdizen, and Luther W. McDonald IV. (2022). Characterization of uncertainties and model generalizability for convolutional neural network predictions of uranium ore concentrate morphology. Chemometrics and Intelligent Laboratory Systems, 225, 104556.
[17]. Külahci F. Spatiotemporal. (2016). four- dimensional modeling and simulation of uranium (238) in Hazar Lake (Turkey) water. Environmental Earth Sciences, 75(452).
[18]. Ambrosino, F., Stellato, L., and Sabbarese, C. (2020). A case study on possible radiological contamination in the Lo Uttaro landfill site (Caserta, Italy). Journal Physics Conferance Series, 1548, 012001. doi: https://dx.doi.org/10.1088/1742-6596/1548/1/012001
[19]. Fabrizio Ambrosino, Lenka Thinová, Miroslav Hýža, and Carlo Sabbarese. (2020). 214Bi/214Pb radioactivity ratio three-year monitoring in rainwater in Prague. Nukleonika, 65(2),115-119. doi: 10.2478/nuka-2020-0018
[20]. Shalaby, M. H. (1990). Uranium mineralization in the northern Gabal Qattar locality, Northern Eastern Desert. 7th Conferance Phanerozoic and Development, Al Azhar University, Cairo, Egypt, 3-19.
[21]. Závodská L., Kosorínová E., Šcerbáková L., and Lesný J (2008). Environmental Chemistry of Uranium. Hej, Env-081221-A, 1-19. http://heja.szif.hu/ENV/ ENV-081221-A/env081221a.pdf
[22]. Roz., M. E. (1994). Geology and uranium mineralization of Gabal Gattar area, North Eastern Desert, Egypt. M.Sc. Thesis, Faculty of Science, Al Azhar University, Cairo, Egypt.
[23]. Abu Zaid., M. M. (1995). Relation between surface and subsurface uranium mineralization and structural features, Gebel Gattar, North Eastern Desert, Egypt. M.Sc. Thesis, Ain Shams University, Cairo, Egypt.
[24]. Mahdy., N. M. (2015). A genetic model for molybdenum and uranium mineralization in Gebel Gattar Granite, North Eastern Desert, Egypt. M.Sc. Thesis, Ain Shams University, Cairo, Egypt.
[25]. Waheeb, A. G. (2021). Resolved shear for the uranium mineralized fault contacts at Gabal Abu Hamr and Gabal Gattar, northern eastern desert, Egypt. Annals of Geological Survey of Egypt. V. XXX VIII, 243-255.
[26]. Yehia Z. Darwish, A. Kh Embaby, Mohamed A. El Zalaky, Darwish M. El Kholy, and Samir M. Selim. (2022). Arbitrary estimation of uranium ore reserves in Qattar–V, Northeastern Desert, Egypt using geographic information system. Journal of Radiation Research and Applied Sciences, 15, 224–231. https://doi.org/10.1016/j.jrras.2022.01.022
[27]. El-Kammar, A.M., Salman, A.E., Shalaby, M.H., and Mahdy, A.I. (2001). Geochemical and genetical constraints on rare metals mineralizations at the central Eastern Desert of Egypt. Chemical Journal, 35, 117–135. https://www.jstage.jst.go.jp/article/geochemj1966 /35/2/35_2_117/_pdf
[28]. Mahdy, M.A., Salman, A.B., and Mahmoud, A.H. (1990). Leaching studies on the uraniferous Hammamat sediments, Wadi Bali, northern estern desert, Egypt. 14th Congress of Mining and Metallergy, Edinburgh Scotlafd, 229-235.
[29]. Mahdy, A.A. (1999). petrological and geochemical studies on the younger granites and hammamat sediments at Gabal Gattar-5 uranium occurrence, wadi Balih, North Easter Desert, Egypt. PhD Thesis, Geology Department, Faculty of Science, Ain shams University, Cairo, Egypt.
[30]. Waheeb, A.G. and El Sundoly, H.I. (2016). Structure roles for the localization of metasomatite uranium deposit type at wadi Belih area, Northern Eastern Desert, Egypt. Egyptian Journal of Petroleum, 25, 201-214.
[31]. Amin, N.F. (2010). Surface and sub-surface structural features controlling uranium mineralizations at granitic-hammamat contact, Wadi Belieh, Northern Eastern Desert, Egypt. PhD Thesis, Faculty of Science, Ain Shams University, Cairo, Egypt.
[32]. Binu, D. and Rajakumar, B. R. Eds.(2021). Artificial intelligence in data mining: Theories and applications. Elsevier Science and Technology, Academic Press, India, 257 P. https://www.researchandmarkets.com/reports/5203956/artificial-intelligence-in-data-mining-theories.
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