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Neural Networks Usability Analysis in Economic Security Indicators Dynamics Forecasting

: The paper is devoted to neural network applicability analysis in economic security indicators forecasting models. Exchange indicators usage makes it possible to introduce tools for economic security operational monitoring, since they largely determine the economic environment dynamics development. Neural networks training and various models comparative analysis for economic time series values predictions were carried out using the dollar / ruble exchange rate example. The paper presents two initial data sets analysis with information content of different amounts. Predictive indicators calculation was carried out using three neural networks different models and gradient boosting method. The results obtained in the work make it possible to identify the best neural network model for target indicators prediction, as well as to analyse neural networks approaches effectiveness’ in the problems under consideration, depending on the dimension of the initial data. Based on the simulation’s results, there is a conclusion, that neural network methods in economic security indicators forecasting can be justified only on a significant sample size.