Financial University under the Government of the Russian Federation (kafedra biznes-analitiki, starshiy prepodavatel')
employee
Russian Federation
VAC 5.2.3 Региональная и отраслевая экономика
VAC 5.2.4 Финансы
VAC 5.2.5 Мировая экономика
VAC 5.2.6 Менеджмент
VAC 5.2.7 Государственное и муниципальное управление
UDK 33 Экономика. Народное хозяйство. Экономические науки
This paper examines the use of neural network modeling in various aspects of business, such as customer behavior analysis, supply chain optimization, financial analysis and personnel management. The emphasis is on the ability of neural networks to analyze and predict based on large amounts of data, thereby improving business decision making. Challenges associated with the implementation of neural networks are also discussed, including requirements for data quality and interpretability of results. Inspired by the structure and function of the human brain, neural network modeling is a powerful tool for analyzing and predicting large data sets. The relevance of this work is due to the fact that decision-making in modern business requires taking into account many factors and variables, where neural networks make it possible to identify trends and patterns, thereby providing more accurate forecasts.
Neural network, modeling, financial analysis, personnel management, forecasting, data array, neural network modeling
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