Data mining model for the study of the system of quotas for the catch of aquatic biological resources

Abstract

Objective. Extraction of aquatic biological resources is an important sector of the Russian economy. Along with the achievement of high economic indicators, which are aimed at harvesters, in the foreground, in addition to production, the requirement to preserve populations and maintain the diversity of aquatic biological resources is also highlighted. Achieving the goals set on the basis of the listed requirements is possible by increasing the efficiency of processing information obtained from operational reports collected by departments of territorial administrations. The lack of automation in the processing of spreadsheets and the generation of analytical reports in manual mode makes it difficult to form a clear generalized picture of the state of the industry. Method. In the present study, methods of data mining analysis, analysis of statistical data were used. Result. A data mining model has been developed to study the system of quotas for catching aquatic biological resources, created in the Loginom program. Conclusion. The developed model allows not only to estimate the levels of development of quotas, but also to predict the levels of development using the arimax module, and also shows the possibility of creating a full-fledged information system for accounting for the extraction of aquatic biological resources based on it.