Universal tool for simulation of complex systems

Abstract

The aim of this study is to determine the criteria of universal simulation tool for complex systems. Objectives of the study is to determine degrees of complexity for different systems. The object of study is the simulation of complex systems. Subject of research: synergetic paradigm of complexity as a tool for identifying and predicting natural and artificial systems. Results of the study: analyzes new approaches to modeling complex systems of different nature. It was shown that synergistic paradigm of complexity has the necessary tools to set universal adequate identification and forecasting of the basic patterns of both natural and artificial systems. These primarily include the theory of fractals, nonlinear dynamics, econophysics, theory of complex networks. Distinguished two classes of problems: (1) the task of comparative classification and (2) monitoring and warning of critical and crisis phenomena. The first class of problems comes down to the selection of so-called measures of system complexity, which make an ability to classify systems by complexity. Also more complex system is a robust, resistant to disturbances. Exploring the dynamics of the selected measures of complexity and comparing it with the original dynamics of a complex system can be built indicators and predictors of critical and crisis phenomena. Conclusion. The effectiveness of the proposed instruments demonstrated by the statistical implementations of complex systems of different nature, presented in the form of time series: physical, technical, financial, biomedical, cognitive and so on. Research results recommended to create decision support systems, in particular for monitoring and forecasting unwanted crisis in complex systems.