Application of artificial intelligence in assessing the prospects of solid mineral deposits

The study presents the development of an ontological model for managing information about the mineral resource base, aimed at improving the efficiency of minerals use. The existing approaches to structuring geological information and methods of ontological modeling in the field of geology are analyzed. The principles of creating semantic networks to classify the knowledge about mineral deposits are studied. It is found out that traditional methods to control mineral resources require modernizing in the context of digitizing the geological industry. The possibilities of using modern semantic web technologies to solve problems of classification and analysis of geological data are studied. The key components of the ontological model are identified, including the taxonomy of deposits, classification of resources, and funding system. The effectiveness of using OWL and RDF standards to create a unified information system is found out. A set of tools for the development and verification of the ontology is created, including Protégé, Apache Jena and SPARQL. A solution is proposed to integrate the ontological model with existing information systems in the field of minerals use. A method is developed for creating an ontology that takes into account the specific features of the geological industry and the requirements for controlling mineral resources. The practical significance of the proposed approach based on testing the model on real data is substantiated. The results of testing the ontological model are presented, confirming its effectiveness in solving problems of field classification and analyzing the state of the mineral resource base.