MODELING OF INTELLECTUAL TECHNOLOGY FOR CALCULATING THE INTEGRAL INDICATOR OF COMPETITIVENESS OF AN E-COMMERCE ENTERPRISE

Abstract

The use of modern achievements of scientific and technological progress is crucial in building information systems and implementing information technologies. Recently, artificial neural networks have been used to solve several data classification and clustering tasks, which allow achieving extraordinary accuracy. The availability of a large number of software and hardware tools for creating and training artificial neural networks, as well as the ability to use a large amount of data (including data from real enterprises) to train networks on it, allows you to quickly build effective models for solving various problems, including economic ones. In today's conditions, tracking and calculating the dynamics of the integral indicator of competitiveness of an e-commerce enterprise is one of the main indicators of the state of the enterprise in the economic space of the state. Accordingly, to calculate and model situations related to the calculation of the dynamics of the integral indicator of competitiveness of an e-commerce enterprise, it is worth applying neural network models for processing and analyzing a large amount of data. This approach allows optimizing enterprise management processes, increasing the personalization of service and ensuring effective interaction with customers, etc. The considered convolutional neural network has such special properties as self-organization, the ability to learn in the process of work, generalization, simulation of processes and phenomena, including nonlinear ones, formation of complex dependencies in the space of diagnostic events, efficiency of work with high-dimensional features, which determine the expediency of their use for solving forecasting problems, in particular, calculation and modeling of situations related to the calculation of the dynamics of the integral indicator of competitiveness of an e-commerce enterprise.