Author:
Соловйов В. М.,Соловйова В. В.
Abstract
From the standpoint of interdisciplinary self-organization theories and synergetics analyzes current approaches to modeling socio-economic systems. It is shown that the complex network paradigm is the foundation on which to build predictive models of complex systems. We consider two algorithms to transform time series or a set of time series to the network: recurrent and graph visibility. For the received network designed dynamic spectral, topological and multiplex measures of complexity. For example, the daily values the stock indices show that most of the complexity measures behaving in a characteristic way in time periods that characterize the different phases of the behavior and state of the stock market. This fact encouraged to use monitoring and prediction of critical and crisis states in socio-economic systems.
Reference27 articles.
1. 1. Малинецкий Г.Г. Теория самоорганизации. На пороге IV парадигмы / Г.Г.Малинецкий // Компьютерные исследования и моделирование. - 2013. - Т.5, №3. - С.315-366.
2. 2. Кун Т. Структура научных революцій / Т.Кун // - М.: АСТ, 2009. - 320 с.
3. 3. Пригожин И. От существующего к возникающему: Время и сложность в физических науках / И.Пригожин. - Перевод с английского. Серия "Синергетика: от прошлого к будущему". Изд.3 URSS, 2006. - 296 с.
4. 4. Barrat A. Dynamical processes on complex networks / Barrat A., Barthelemy M., Vespignani A. // Cambridge University Press, 2008. - 347 p.
5. 5. Halvin S., Cohen R. Complex networks. Structure, robustness and function / Halvin S., Cohen R. // Cambridge University Press, 2010. - 238 p.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献