MAIASP. 2025. No. 19 Vladimir Danilov (Saratov, Russia), Valeriia Morozova (Saratov, Russia), Mariia Rastegaeva (Saratov, Russia), Alexei Fedorov (Saratov, Russia) EXPERIENCE IN THE USE OF MACHINE LEARNING FOR THE IDENTIFICATION OF BURIAL MOUNDS Modern machine learning methods offer new opportunities for enhancing the efficiency of analysis and accuracy of barrow identification. The study involves the application of machine learning algorithms, mathematical-cartographic modeling methods, and GIS technologies for analyzing large volumes of lidar survey data, which contributes to the automation of the process and the identification of hidden patterns. The testing of the mound search method was conducted in the areas of archaeological sites, specifically the Bronze Age settlement “Krasavka Station” and a group of mounds (2 barrows) near the ancient settlement “Taman-3” (a federal cultural heritage site “Settlement-3” and a group of mounds (2 barrows)). The use of automated data analysis algorithms allows reducing the time for their interpretation, opening up new horizons in archaeology and contributing to the effective preservation of cultural heritage. The results of the work are cartographic models indicating potential barrow locations on the territory of the monuments. Key words: laser scanning, DTM (Digital Terrain Model), GIS, machine learning, mathematical-cartographic modeling, search for mounds, Bronze Age settlement Krasavka Station, ancient rural settlement Taman-3. |