DETERMINING THE CORRELATION BETWEEN DATASETS FOR CALCULATION OF THE RETAIL PRICE WHEN USING SOFTWARE AGENTS

The development and support of algorithms for calculating prices in the field of trade is one of the current trends in the development of information systems in recent years, which attracts the attention of specialists of various profiles. Experts in the field of economics see in such algorithms new opportunities for improving automated systems, transforming them into public automated systems of a new generation with advanced means of presenting various digital information resources and accessing them, created taking into account the need for integration and the use of APIs. Within the framework of the outlined problem, the scientific tasks of developing models, methods, algorithms and programs that simulate processes for data processing and price calculation in order to determine their main characteristics for the construction of mathematical software for automated retail price calculation systems are important [12]. In general, effective pricing contributes to the subordination of production to social needs, and an adequate level of prices contributes to economic growth, provides an effective competitive environment and orients production to innovative content [1]. The above determines the relevance of the development and improvement of algorithms for calculating the retail price of a product in the event, that already known algorithms determine the price inaccurately (for example, when there is insufficient amount of necessary data due to certain factors). The use of the latest ones in such situations quite often increases the risk of selling the product at an irrelevant price, which in turn can lead to a decrease in turnover or loss of funds.