The purpose of the article is to research, analyze and consider general problems and prospects for the development of management systems for learning processes with the ability to support distance learners using the latest technologies. The research methodology consists in methods of semantic analysis of the basic concepts of this subject area (management systems of educational processes). The article considers the approaches to the development and operation of the learning management system. The scientific novelty of the research is the analysis of the functioning of modern learning management systems and learning systems, the results of which can be used in the development of their own learning management system, which is relevant in today’s online learning environment. Conclusions. The paper considers well-known views on distance learning and analyzes modern information systems for distance learning management. Taking into account the results of the analysis, the authors decided to develop an information system for managing educational processes in distance education.

The article deals with current problems of ontological modeling of processes of design, construction and operation of buildings and structures in transport infrastructure. Such modeling involves use of standards and classifiers adopted in Europe and harmonized within BIM (Building Information Modeling) and EULYNX (European railway technology alliance). Multi-level ontological model of transport infrastructure is proposed. This model contributes to formation of understanding of essence of subject area, which is the field of transport infrastructure (transport repair enterprises, transport facilities (bridges, tunnels, tracks), transport depots, stations, etc.). Proposed model contributes to presentation of knowledge in form that is convenient for their processing in intelligent systems, ensuring intellectualization and digitization of processes in transport infrastructure. Proposed ontological approach ensures multiple use of knowledge and existing ontologies, allows the use of modern technologies (in particular, semantic ones), when objects of subject area correspond to their reflections in multi-level ontological model. Ontological approach to modeling of transport infrastructure makes it possible to move to automatic management of these objects and corresponding processes in systems that ensure intellectualization and digitalization of transport and transport infrastructure. Developed multi-level ontological model is planned to be supplemented with new components, imposing appropriate restrictions.

The article considers topical problems of modeling control processes in intelligent systems in transport. Management of such systems also involves control and monitoring of the processes of their design and maintenance. The article proposes an ontological model of process control of intelligent systems in transport. The proposed ontological model is necessary for the formation of a common understanding of the essence of the subject area, which is the transport sphere (transport systems, transport enterprises, vehicles and transport infrastructure). The proposed ontological model contributes to the presentation of knowledge in a form that is convenient for their processing in the intelligent system of transport; ensuring the possibility of obtaining and accumulating new knowledge. The proposed ontological approach provides multiple use of knowledge and previously developed ontologies. The proposed approach allows the use of modern multi-agent technology, when each agent has its own ontological model. The considered ontological approach to modeling of management of intelligent systems allows to pass to automatic control of processes in these systems (in the presence of the corresponding restrictions). The developed ontological model of the subject area is planned to be expanded and supplemented with new components, imposing appropriate restrictions. The OWL software code obtained from the simulation results in Protégé can be further used within the knowledge base of the intelligent system, processing this information in various software applications, including Java applications.

The purpose of the article is to research, analyze, and consider current problems and prospects for the development of software for the recognition of transport objects based on the use of pattern recognition theory, methods, and tools of artificial intelligence, and different types of neural networks. The research methodology is basic methods and algorithms of pattern recognition, methods and means of artificial intelligence, and different types of neural networks. The article considers the main problems of intellectualization of processes occurring in transport. The main attention is paid to the intellectualization of the processes of transport objects’ recognition. The article analyzes the most common recognition methods. A study of these methods and approaches to the recognition of moving vehicles is conducted. It is determined which methods have high and which have low computational complexity. Among the considered methods are those that recognize static transport objects (primarily transport infrastructure objects) using intelligent technologies, statistical, probabilistic, and other methods. The main attention is paid to methods that recognize dynamic transport objects. The basis of intellectualization of the processes of recognition of this group of objects is the use of neural networks, in particular convolutional, recurrent, neural networks with long short-term memory (LSTM), etc. The scientific novelty of the research is the analysis of modern methods of moving transport objects’ recognition, the results of which can be used in the development of their software product. The article emphasizes that the proposed modern approach to the recognition of transport objects (moving vehicles and transport infrastructure) involves solving a wide range of problems based on the use of intelligent technologies, in particular neural networks. Conclusions. The most common methods for solving current problems of recognition of transport objects (vehicles and transport infrastructure) have been investigated and analyzed. Based on the analysis of methods for recognizing moving vehicles, it has been determined which methods have high and low computational complexity. The basis of the intellectualization of the recognition processes for this group of transport objects is the use of various neural networks.

The article considers an ontological approach to the creation and use of learning information systems and learning process management systems that operate in a cloud environment. The proposed ontological approach provides an opportunity to implement learning processes, supporting the sharing of both users (students, teachers, methodologists, etc.) and different training courses of common learning content stored in the cloud. The result of using cloud technologies and ontologies is the ability to make the necessary adjustments to the set of goals and objectives of the learning process, the learning process, the course, the requirements for the level of knowledge and competence of students. An ontological approach to building learning systems operating in a cloud environment is proposed. It is advisable to use the developed ontological model when implementing learning system in managing learning processes in higher educational institutions. The constructed ontological model provides an opportunity to implement continuous improvement of learning processes, supporting the sharing by both users (students, teachers, methodologists, etc.) and different training courses of common training content stored in the cloud. The result of using cloud technologies and ontologies is the possibility of making the necessary adjustments to the set of goals and objectives of the learning process, to the learning process, the training course, to the requirements for the level and competencies of trainees on the part of employers and / or the state. The developed ontological model of learning processes allows, using cloud technologies, to form a space of learning content. Sharing learning content across learning systems has not only enabled the use of ready-made, high-quality learning materials developed by the best teachers, but also reduced the time and resources spent on transferring content from one system to another. The proposed approach uses the integration of technologies such as: ontological modeling, intellectualization and informatization, as well as cloud technologies. The use of these technologies makes it possible to predict the occurrence of emergency situations in the learning process.