METHODOLOGY FOR EVALUATING THE EFFECTIVENESS OF A COMMERCIAL ORGANIZATION
In modern conditions of digital technologies, most economic problems are solved with the help of mathematical models, due to their complexity, through the use of image recognition technology (computer learning) based on the use of neural networks. Neural networks are especially important in the implementation of such a complex task as forecasting economic processes. Neural network technologies are an indispensable tool for high-quality processing of big data, without which it is quite difficult or even impossible to make full-fledged economic forecasting and effective management decisions. Currently, the technologies of neural networks used in the framework of artificial intelligence make it possible not only to simplify economic forecasting in the conditions of digital data, but also to increase its accuracy. Therefore, interest in the use of artificial neural network technologies in solving economic problems, including forecasting financial and economic processes, is increasing daily. The article discusses the concept and properties of neural networks, as well as the tasks of neural networks as a tool for forecasting economic processes. The disadvantages of neural networks for forecasting due to the complexity of their training and use are revealed. Neural networks in the economy are especially in demand in conditions of instability of the development of economic processes.