Research of modern methods and tools of ontological engineering in the context of creating intellectual systems - Dolhyi, Andrii; Shubin, Ihor (INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, 2025)
The subject of the work is the study of modern methods and tools of ontological engineering in the context of developing intelligent systems. In particular, ontological engineering as a process of creating formalized knowledge bases for intelligent systems. The work analyzes ontological modeling languages (RDF, OWL, SWRL, etc.), the SPARQL query language and tools such as Protégé, Hozo, etc., which allow implementing the specified approach. The purpose of the research is to identify and analyze modern tools and methods of ontological engineering for developing knowledge bases that provide high prediction accuracy and adaptability in complex intelligent systems using artificial intelligence or other prediction algorithms. The objective of this study is to conduct a comprehensive analysis of modern methods and tools of ontology engineering, including a comparative description of their capabilities and limitations when applied in intelligent systems. The study involves studying methods for automating the processes of creating and updating ontologies, in particular using deep learning and natural language processing, as well as evaluating promising languages and tools for modeling ontology. Particular attention is paid to the analysis of the application of ontologies in various subject areas where high forecasting accuracy is required, with further research into methods for optimizing queries to ontological databases. The practical part of the work involves creating a demonstration ontological knowledge base for an intelligent control system for virtual distributed power plants, which will allow assessing the practical value of the study. The research methods include a thorough analysis of the literature and available documentation on the topic, a comparative analysis of the obtained data and further demonstration in practice of the application of selected tools and methods, based on their indicators. Results The issue of the feasibility of ontological engineering in modern intelligent systems is considered. Tools and methods for creating knowledge bases based on ontologies are presented and analyzed. The paper provides comparative statistics of modern tools for creating ontologies. A substantiated vision of the situation around the tools and methods of ontological engineering was put forward. The limitations and unique aspects of each of the considered tools are revealed. Optimal approaches to creating knowledge bases for intelligent systems are determined. The use and features of ontological engineering tools are demonstrated on a practical example in the context of intelligent systems for controlling virtual distributed power plants. In conclusion, the novelty of the study lies in the modernity of the view on the issue of choosing tools for creating knowledge bases using ontological engineering, in particular in terms of their use in intelligent systems, in combination with artificial intelligence.The results of this work can be used in the development of relevant intelligent systems that use knowledge bases. The study provides a wide range of information and comparisons of ontological engineering approaches and tools.