кафедра обліку і оподаткування

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Browsing кафедра обліку і оподаткування by Author "Погорелов, Ю. С."

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    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.