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Item Developing Ukrainian Enterprises Using Neural Networks(СНУ ім. В. Даля, 2024) Pohorelova, K. А.; Pogorelov, Y. S.; Погорелова, К. А.; Погорелов, Ю. С.The article explores the features of using neural networks for the development of Ukrainian enterprises. It examines the theoretical foundations of neural networks, their history, types, and examples of application in various industries. Special attention is given to analyzing the factors influencing enterprise development, such as technological innovations, economic conditions, organizational changes, competition level, and market conditions. It is shown that technological progress is a key factor in the development of enterprises in the modern world. The current state of development of Ukrainian enterprises is investigated in the context of adapting to new economic conditions, particularly during the war. The war in Ukraine significantly affects the economy, including the business sector. Internal challenges include political instability, economic reforms, workforce shortages due to mobilization, power outages, and the need for modernization of production facilities. External factors include global competition, the influence of international markets, and economic sanctions. Despite the challenging conditions, Ukrainian enterprises have growth opportunities through the implementation of the latest technologies, such as neural networks. The main challenges and opportunities for Ukrainian business are analyzed, and the directions for using neural networks for enterprise development are proposed for each development factor, considering the specifics of business operations in Ukraine. Specific examples of successful implementation of neural networks in the banking sector (PrivatBank), IT companies (SoftServe), and the agro-industrial complex (MHP) are provided. The article analyzes the advantages and disadvantages of using neural networks, such as increased efficiency, forecasting accuracy, service personalization, risk reduction, and challenges related to high costs, integration complexity, lack of qualified personnel, and data quality dependency. The prospects for enterprise development using neural networks are considered: productivity improvement, product and service quality enhancement, efficient resource management, risk reduction, innovative development, market adaptation, and resilience support. It is proven that the use of neural networks has significant potential for transforming enterprises, making them more efficient, flexible, and innovative.Item Problems of Forming Competitive Regional Innovation Systems(СНУ ім. В. Даля, 2024) Serikova, O. M.; Syvochka, V. V.; Fomenko, D. V.; Серікова, О. М.; Сивочка, В. В.; Фоменко, Д. В.The creation of conditions for the development of integrated research, education and business complexes will be possible through the interaction of political, regulatory, economic, social and cultural factors. Political conditions are determined at the state level. At the same time, the integration of education, science and innovative business has faced some problems, in particular, related to governance. Therefore, the main task at present is to ensure real integration in these sectors in order to ensure innovative transformations not only in the economy but also in society as a whole, and the ministry should restructure the management of these areas to adequately meet this task. For example, the project to modernize universities envisages that they should become a place where people are trained to perceive innovative ideas, to be formed into specialists in a new way, and to be the driving force behind innovative development. It has also become clear that it is necessary to move from training specialists in mass professions to training specialists capable of ensuring the operation of modernized enterprises and enterprises that use innovative technologies aimed at producing innovative products. The vocational education system has already begun to restructure in this direction, with resource centers emerging that bring together primary, secondary, and higher vocational education institutions to build a chain of training for all levels of personnel focused on advanced manufacturing. At the present stage, the problems of integrated formation and development of science and education are being solved, but the mechanism of systemic influence through the creation of integrated regional research and education complexes - research (leading) universities of a new type - is not used. The experience of implementing integration processes of academic and university science and production shows that the development of a specific model and its organizational and legal formalization require resolving the issues of identifying the lead organization and coexecutors, which will determine the type of integration model, scientific, educational, social, environmental and other problems to be solved. In this case, it is important to choose the organizational and legal form of interaction between the structures formed as part of the new entity, the distribution of responsibilities of all participants in addressing issues of staffing, inventory and equipment, financing for each participant through an interconnected system of legal documents and regulations, reporting, etc.