Digital Ai "Decision Tree" for Predicting Russian GDP Value Based on Big Data Mining to Ensure Balanced and Sustainable Economic Growth

Abstract

The relevance of the research study is due to the fact that the article attempts to prove or falsify the hypothesis that the "AI-Decision Tree" neural network model makes it possible to obtain a forecast of Russia's GDP for various scenarios. Various aspects of the AI application in the field of big data processing, deep learning and forecasting have been investigated in the article. However, experience has proven that, certain issues of using artificial intelligence require further scientific research in order to achieve a balanced and sustainable growth of the financial and economic system. Theoretical foundations of sustainable economic growth in the country have been studied. The authors have reviewed modern domestic and foreign literature on the topic and paid special attention to the issues of balanced financial and economic system and sustainable economic growth in modern conditions. We demonstrate the factors increasing risk and market uncertainty and other in order to achieve a balanced and sustainable growth of the financial system based on the AI-system "Decision Tree" developed. The trends in functioning of the financial and economic system have been determined; the dynamics of the balanced profit volumes in real sector organizations has been traced quarterly for the period of 2015-2018. Live data of the Federal State Statistics Service showed that the balanced financial result (profit except for loss) of organizations (apart from small business entities, banks, insurance organizations and state and municipal institutions) in current prices decreased by 8.5% in 2017. In order to visualize the dynamics of the effective factor - GDP a neural network model "AI-quantization of data" has been developed. In order to achieve a balanced and sustainable growth of the financial system based on the AI-system "Decision Tree" developed.