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Dynamic Models of Self-organization Through Mass Behavior in Society

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Proceedings of the Second International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’17) (IITI 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 679))

Abstract

Second-order cybernetic models let explain an influence of mass behavior upon macroeconomic characteristics. In particular, we consider situations related to the self-organization and synergy of interacting socio-economic systems and an impact of random factors. In such situations catastrophic intensity of offensive adaptive mass behavior may produce a negative impact on the economic stability. Nonlinear dynamics of self-organization processes complicates prediction of macroeconomic characteristics via extrapolation of trends. An amplitude-frequency analysis of oscillatory self-organization processes let obtain more relevant forecasts.

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Acknowledgments

The research described in this paper is partially supported by the Russian Humanitarian Found (grants 15-04-00400), the Russian Foundation for Basic Research (grants 15-07-08391, 15-08-08459, 16-07-00779, 16-08-00510, 16-08-01277, 16-29-09482-ofi-i, 17-08-00797, 17-06-00108, 17-01-00139, 17-20-01214), grant 074-U01 (ITMO University), project 6.1.1 (Peter the Great St. Petersburg Politechnic University) supported by Government of Russian Federation, Program STC of Union State “Monitoring-SG” (project 1.4.1-1), state order of the Ministry of Education and Science of the Russian Federation №2.3135.2017/K, state research 0073–2014–0009, 0073–2015–0007, International project ERASMUS +, Capacity building in higher education, № 73751-EPP-1-2016-1-DE-EPPKA2-CBHE-JP, Innovative teaching and learning strategies in open modeling and simulation environment for student-centered engineering education.

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Authors and Affiliations

  1. St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS), 14th Lin. V.O., 39, St. Petersburg, 199178, Russia

    Boris Sokolov & Dmitry Verzilin

  2. Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University), Kronverksky pr., 49, St. Petersburg, 197101, Russia

    Boris Sokolov & Tatiana Maximova

  3. Lesgaft National State University of Physical Education, Sport and Health, Dekabristov 35, St. Petersburg, 190121, Russia

    Dmitry Verzilin

  4. St. Petersburg State University, Universitetskayz emb., 7-9, St. Petersburg, 199034, Russia

    Irina Sokolova

Authors
  1. Boris Sokolov
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  2. Dmitry Verzilin
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  3. Tatiana Maximova
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  4. Irina Sokolova
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Corresponding author

Correspondence to Dmitry Verzilin .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR labs), Auburn, Washington, USA

    Ajith Abraham

  2. Rostov State Transport University , Rostov-on-Don, Russia

    Sergey Kovalev

  3. Bauman Moscow State Technical University , Moscow, Russia

    Valery Tarassov

  4. VSB-Technical University of Ostrava , Ostrava, Czech Republic

    Vaclav Snasel

  5. Department Electrical Power Engineering, Technical University of Varna, Varna, Bulgaria

    Margreta Vasileva

  6. Rostov State Transport University , Rostov-on-Don, Russia

    Andrey Sukhanov

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Sokolov, B., Verzilin, D., Maximova, T., Sokolova, I. (2018). Dynamic Models of Self-organization Through Mass Behavior in Society. In: Abraham, A., Kovalev, S., Tarassov, V., Snasel, V., Vasileva, M., Sukhanov, A. (eds) Proceedings of the Second International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’17). IITI 2017. Advances in Intelligent Systems and Computing, vol 679. Springer, Cham. https://doi.org/10.1007/978-3-319-68321-8_12

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  • DOI: https://doi.org/10.1007/978-3-319-68321-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68320-1

  • Online ISBN: 978-3-319-68321-8

  • eBook Packages: EngineeringEngineering (R0)

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