Research of the Russian Federation science perspectives by model

The analysis of the development of the scientific industry is made. Its relevance is justified. Importance of science in obtaining fundamentally new knowledge, searching for answers to the so-called big challenges of tomorrow, which is set by the state, is proved. The purpose of the work is to build a predictive model of the general state of the scientific branch of the Russian Federation to decision support and to obtain forecasts for the near future. Various types of models are analyzed. Their main advantages and disadvantages in relation to the research topic are identified. The public statistical service of the Federal State Statistics Service was used as a source of data on the object under study. Private criteria and factors potentially influencing the object were selected from the number of publicly available annual statistical series: the number of patent applications filed, internal research and development costs, developed advanced production technologies, the number of organizations leading the training of graduate students, doctoral students, etc. Estimated indicators summary used as a general criterion are: the number of patents, the number of researchers with a degree and used advanced manufacturing technologies. The mutual correlation of factors is investigated. A linear multifactor model of the object dynamics is constructed. It is shown this one cannot be used to predict the object due to the poor quality of the prediction. A second-order regression-differential model with a good quality of post-prediction is constructed. The forecast of the dynamics of changes in the object for the next three years is created. The influence of changes in controllable and uncontrollable factors on the object is investigated. It is shown that without application of effort, the scientific branch will worsen performance in next years, but this can be improved by increasing costs and increasing the admission of graduate students.