Application of artificial intelligence for commodity identification for customs purposes - Galina Yu. Fedotova; Anna Yu. Komelova (Цифровая экономика и инновации)
Application of artificial intelligence in various spheres of life is a critical task. International trade is not an exception for the introduction of innovations. The key issue of inter-country movement is the commodity identification for customs purposes. The paper presents the results of a comprehensive practical comparative study of the possibility of using artificial intelligence to classify commodities for customs purposes. As a model, the neural network of artificial intelligence developed by the World Customs Organization is used. The study included four stages, including the selection of goods to improve the reliability of the results obtained, a study of the applicability of the model for classifying commodities and the possibility of its use for customs purposes, as well as a criteria analysis of the features taken into account by the model when classifying commodities. The limited applicability of the model proposed by the World Customs Organization was revealed both for identification based on classification and for customs purposes based on direct analysis of the texts of the Harmonized Commodity Description and Coding System. The model does not see the degree of completeness in the descriptions of commodities, does not take into account the feature of independence of the goods in terms of use. An increase in the number of words in the description of the commodities also reduces the likelihood of its correct identification. The model takes into account most successfully the characteristics of goods related to the scope of application and functional purpose. The result of the complex study allowed considering comprehensively the possibilities of practical application of artificial intelligence and evaluating the actually obtained results for the studied group of goods. The obtained data on identifying the classification features of commodities taken into account in the model can be used for its further development.