APPLICATION OF ANALYTICAL TECHNIQUES AND MACHINE LEARNING MODELS FOR THE IDENTIFICATION AND CULTURAL ATTRIBUTION OF ANCIENT POTTERY: A CASE STUDY FROM BOLU CLAUDIOPOLIS, TURKEY
DOI:
https://doi.org/10.14795/jaha.13.1.2026.1504Keywords:
Ancient Pottery, XRF Analysis, Machine Learning, Bolu Claudiopolis, Fuzzy LogicAbstract
Understanding the origin, manufacturing technology, and cultural connections of ancient pottery is a primary goal in interdisciplinary research spanning archaeology and materials science. This study investigated 20 pottery samples from the ancient site of Bolu Claudiopolis (modern-day Bolu, Turkey). For a detailed and multifaceted analysis, a combination of scientific techniques—including X-ray Fluorescence (XRF), X-ray Diffraction (XRD), and Fourier Transform Infrared Spectroscopy (FTIR)—were employed to obtain the chemical, mineralogical, and structural characteristics of the pottery. The resulting data were input into various machine learning algorithms (KNN, SVM, Random Forest) implemented using Weka software. Principal Component Analysis (PCA) was utilized for dimensionality reduction and pattern discovery. To enhance accuracy in identifying and distinguishing possible civilizational origins (Roman and Greek), Fuzzy Logic was applied to define rules for combined classification. Furthermore, data fusion methods were used to combine and analyze information across different data levels (chemical, mineral, structural). The results demonstrated significant differences in the chemical and mineral composition of the samples, which can be interpreted in relation to different civilizations. The Random Forest model showed the highest classification accuracy. Fuzzy analysis indicated that most samples had a high dependency on the Roman civilization, while some exhibited a mixed tendency toward the Greek civilization. XRD and FTIR results suggested the use of a medium firing temperature and silicate soils with specific mineral granules. This study exemplifies a new interdisciplinary approach that utilizes advanced scientific techniques and machine learning to enable a deeper analysis of ancient pottery and its civilizational provenance.
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References
ARASHEED/QASIM/BARLA 2023
Rasheed, N. A./Qasim, O. M./Barla, A. K., Selecting the Important Features to Classify the Archaeological Fragments by Using Statistical Tools, Indian Journal of Computer Science and Engineering 14/3, 472–9. DOI: 10.21817/indjcse/2023/v14i3/231403090.
BAYAZIT/KAYNAK/COŞKUN 2023
Bayazit, M./Kaynak, E./Coşkun, N., Chemical And Mineralogical Analyses Of The Late Neolithic Ceramics From Şah Valley (Singuber), Turkey, Journal Of Scientific Reports-A 052, 327–351. DOI: 10.59313/jsr-a.1206576.
BICKLER 2018
Bickler, S. H., Machine Learning Identification And Classification Of Historic Ceramics. Archaeology 20, 20-32.
CECCARELLI et alii 2018
Ceccarelli, L./Bellotto, M./Pietro, Caruso, M./ Cristiani, C./Dotelli, G./Gallo Stampino, P./Gasti, G./Primavesi, L., Characterization of clays and the technology of Roman ceramics production, Clay Minerals 53/3, 413–429.
CHEN/CHEN 2024
Chen, W./Chen, D., Research on the classification of ancient silicate glass artifacts based on machine learning, Archaeometry.
DI ANGELO/DI STEFANO/PANE 2017
Di Angelo, L./Di Stefano, P./Pane, C., Automatic dimensional characterisation of pottery, Journal of Cultural Heritage 26, 118–28.
ERAMO et alii 2004
Eramo, G./Laviano, R./Muntoni, I. M./Volpe, G., Late Roman cooking pottery from the Tavoliere area (Southern Italy): Raw materials and technological aspects, Journal of Cultural Heritage 5/2, 157–65. DOI: 10.1016/j.culher.2003.05.002.
GIANNOSSA/FORLEO/MANGONE 2021
Giannossa, L. C./Forleo, T./Mangone, A., The distinctive role of chemical composition in archaeometry. the case of apulian red figure pottery, Applied Sciences (Switzerland), MDPI AG. DOI: 10.3390/app11073073.
IKEOKA et alii 2018
Ikeoka, R. A./Appoloni, C. R./Rizzutto, M. A./Bandeira, A. M., Computed Radiography, PIXE and XRF analysis of pre-colonial pottery from Maranhão, Brazil, Microchemical Journal 138, 384–9. DOI: 10.1016/j.microc.2017.12.020.
JIA/CHEN 2025
Jia, X./Chen, Y., Machine Learning-Based Comprehensive Analysis of Phase, Composition, and Microstructure of Yuan Dynasty Oil-Glazed Porcelain, Iranian Journal of Chemistry and Chemical Engineering 44/2, 583–99.
KAHVECİ/PEKŞEN 2023
Kahveci, G./Pekşen, O. Glass Production and Use in Ancient Mesopotamia, Egypt and Anatolia, Erzurum Teknik Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 17, 91-108. DOI: 10.29157/etusbed.1291241.
KAŁUŻNA-CZAPLIŃSKA et alii 2017
Kałużna-Czaplińska, J./Rosiak, A./Grams, J./Chałupka, K./Makarowicz, P./Maniukiewicz, W./Szubiakiewicz, E., The studies of archaeological pottery with the use of selected analytical techniques, Critical Reviews in Analytical Chemistry 47/6, 490-498. DOI: 10.1080/10408347.2017.1334534
KEAWSAWASVONG/LAI 2021
Keawsawasvong, S./Lai, V. Q., End bearing capacity factor for annular foundations embedded in clay considering the effect of the adhesion factor, International Journal of Geosynthetics and Ground Engineering 7/1, 15. DOI: 10.1007/s40891-021-00261-2.
LING/DELNEVO/MIRRI 2023
Ling, Z., Delnevo, G./Mirri, S., Finding on Machine Learning Approaches for Classification of Ancient Ceramics-A Systematic Literature Review. DOI: 10.21203/rs.3.rs-3461328/v1.
LING et alii 2024
Ling, Z./Delnevo, G./Salomoni, P./Mirri, S., Findings on machine learning for identification of archaeological ceramics: A systematic literature review, IEEE Access 12, 100167-100185.
LIU et alii 2023
Liu, C./Wang, W./Wang, H./Zhu, C./Ren, B., A Review on Removal of Iron Impurities from Quartz Mineral, Minerals 13/9, 1128. DOI: 10.3390/min13091128.
LIU/TIAN/CHEN 2024
Liu, Y./Tian, Y./Chen, K., Archaeometric study of the iron objects from the Xuechi sacrificial site and its implication for bloomery iron smelting during early Western Han period in China, Archaeometry 66/5, 1050-1062. DOI: 10.1111/arcm.12952.
LONČARIĆ/COSTA 2023
Lončarić, V./Costa, M., Known glass compositions in Iron Age Europe—Current synthesis and emerging questions, Heritage 6/5, 3835-3863. DOI: 10.3390/heritage6050204.
MOHAMMED/ALMASHHADANI 2023
Mohammed, R./Almashhadani, H., Synthesis, characterization and thermodynamic study of a polymer nanocomposite from methyl acrylate and zirconium chloride as an anti-corrosion coating for carbon steel. Intonational Journal of Corrosion and Scale Inhibition 12, 1180-1191. DOI: 10.17675/2305-6894-2023-12-3-21.
MU et alii 2019
Mu, T./Wang, F./Wang, X./Luo, H., Research on ancient ceramic identification by artificial intelligence, Ceramics International 45/14, 18140-18146. DOI: 10.1016/j.ceramint.2019.06.003.
NAKAMURA et alii 2016
Nakamura, S./Ota, K./Shibuya, Y./Noguchi, T., Role of a water network around the Mn4CaO5 cluster in photosynthetic water oxidation: a Fourier transform infrared spectroscopy and quantum mechanics/molecular mechanics calculation study, Biochemistry 55/3, 597-607.
NAVARRO et alii 2021
Navarro, P./Cintas, C./Lucena, M./Fuertes, J. M./Delrieux, C./Molinos, M., Learning feature representation of Iberian ceramics with automatic classification models, Journal of Cultural Heritage 48, 65-73. DOI: 10.1016/j.culher.2021.01.003.
PAN et alii 2011
Pan, Y. X./Mei, D./Liu, C. J./Ge, Q., Hydrogen adsorption on Ga2O3 surface: a combined experimental and computational study, The Journal of Physical Chemistry C 115/20, 10140-10146. DOI: 10.1021/jp2014226.
PAPACHRISTODOULOU et alii 2006
Papachristodoulou, C./Oikonomou, A./Ioannides, K./Gravani, K., A study of ancient pottery by means of X-ray fluorescence spectroscopy, multivariate statistics and mineralogical analysis, Analytica Chimica Acta 573, 347-353. DOI: 10.1016/j.aca.2006.02.012.
PEACOCK 1970
Peacock, D. P., The scientific analysis of ancient ceramics: a review, World Archaeology 1/3, 375-389. DOI: 10.1080/00438243.1970.9979454.
QI et alii 2022
Qi, Y./Qiu, M. Z./Jing, H. Z./Wang, Z. Q./Yu, C. L./Zhu, J. F./Wang, T., End-to-end ancient ceramic classification toolkit based on deep learning: A case study of black glazed wares of Jian kilns (Song Dynasty, Fujian province), Ceramics International 48/23, 34516-34532. DOI: 10.1016/j.ceramint.2022.08.033.
RASDI et alii 2017
Rasdi, N. M./Fen, Y. W./Omar, N. A. S./Azis, R. A. S./Zaid, M. H. M., Effects of cobalt doping on structural, morphological, and optical properties of Zn2SiO4 nanophosphors prepared by sol-gel method, Results in physics 7, 3820-3825. DOI: 10.1016/j.rinp.2017.09.057
RUSCHIONI et alii 2023
Ruschioni, G./Malchiodi, D./Zanaboni, A. M./Bonizzoni, L., Supervised learning algorithms as a tool for archaeology: Classification of ceramic samples described by chemical element concentrations, Journal of Archaeological Science: Reports 49, 103995. DOI: 10.1016/j.jasrep.2023.103995
SALISU/ALMAJIR 2020
Salisu, B. D./Almajir, I. R., Aflatoxins and aflatoxigenic fungal contamination of common poultry feed products in Katsina State, Nigeria, Novel Research in Microbiology Journal 4/1, 653-665.
SPARAVIGNA 2014
Sparavigna, A. C., Ancient Technologies: The Egyptian Sintered¬ Quartz Ceramics, PHILICA.COM Article number 426.
SUN et alii 2020
Sun, H./Liu, M./Li, L./Yan, L./Zhou, Y./Feng, X., A new classification method of ancient Chinese ceramics based on machine learning and component analysis, Ceramics International 46/6, 8104-8110. DOI: 10.1016/j.ceramint.2019.12.037.
VOLL et alii 2001
Voll, D./Lengauer, C./Beran, A./Schneider, H., Infrared band assignment and structural refinement of Al-Si, Al-Ge, and Ga-Ge mullites, European Journal of Mineralogy 13/3, 591-604. DOI: 10.1127/0935-1221/2001/0013-0591.
WU et alii 2020
Wu, Z./Liu, W./Zheng, J./Li, Y., Effect of methane hydrate dissociation and reformation on the permeability of clayey sediments, Applied energy 261, 114479. DOI: 10.1016/j.apenergy.2019.114479.
YIĞITPAŞA 2023
Yiğitpaşa, D., Re-Assessment of the Claudiopolis stadion rescue excavation in 2008, Journal of Ancient History and Archaeology 10/4, 64-85. DOI: 10.14795/j.v10i4.969.
YIĞITPAŞA 2024
Yiğitpaşa, D., New archaeological data from Claudiopolis in the light of stadion excavations, Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi 14/4, 1321-1339. DOI: 10.48146/odusobiad.1313024.
ZAMPIERIN et alii 2024
Zampierin, D./Moita, P./Lischi, S./van Aerde, M./Barrulas, P./Mirao, J., A multi‐analytical approach applied to pottery from Oman as a key to understanding ancient Indian Ocean maritime trade, Archaeometry 66/5, 967-1015. DOI: 10.1111/arcm.12949.
ZANIER et alii 2024
Zampierin, D./Moita, P./Lischi, S./van Aerde, M./Barrulas, P./Mirao, J., A multi‐analytical approach applied to pottery from Oman as a key to understanding ancient Indian Ocean maritime trade, Archaeometry 66/5, 967-1015. DOI: 10.1111/arcm.12949.
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