Sergiy Solntsev

The study aims to improve methodical approach for formalizing the sustainable development models for progressive countries by suggesting the relevant representative indicators. The study is performed using the statistical approach to determine the suitability of data for further modeling using indicators of variation, taking into account the normality of the population distribution as the main criteria of the data set quality. The study highlights the results of processing measurable quantitative economic, social, and environmental indicators of different countries that may be used for identifying possible changes in the world’s sustainable development. The authors select the indicators for scenario modeling of the sustainable development of Brazil, India, China, Republic of Korea, and the USA, as well as suggest a set of relevant affecting factors. To confirm the meaningful impact of different factors, such as biological balance, conflicts intensity, corruption perception and other, a neural network is developed, and its preliminary training on the test data is conducted. The obtained results can be used to predict economic changes in the world under the influence of specific economic, social, and environmental factors.