IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i12p1396-d576039.html
   My bibliography  Save this article

Study of Synergistic Effects in Complex Stochastic Systems

Author

Listed:
  • Gurami Tsitsiashvili

    (Institute for Applied Mathematics, Far Eastern Branch of Russian Academy Sciences, Radio Str. 7, IAM FEB RAS, 690041 Vladivostok, Russia)

Abstract

In this paper, a method for detecting synergistic effects of the interaction of elements in multi-element stochastic systems of separate redundancy, multi-server queuing, and statistical estimates of nonlinear recurrent relations parameters has been developed. The detected effects are quite strong and manifest themselves even with rough estimates. This allows studying them with mathematical methods of relatively low complexity and thereby expand the set of possible applications. These methods are based on special techniques of the structural analysis of multi-element stochastic models in combination with majorant asymptotic estimates of their performance indicators. They allow moving to more accurate and rather economical numerical calculations, as they indicate in which direction it is most convenient to perform these calculations.

Suggested Citation

  • Gurami Tsitsiashvili, 2021. "Study of Synergistic Effects in Complex Stochastic Systems," Mathematics, MDPI, vol. 9(12), pages 1-14, June.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:12:p:1396-:d:576039
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/12/1396/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/12/1396/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Antonio Majdandzic & Lidia A. Braunstein & Chester Curme & Irena Vodenska & Sary Levy-Carciente & H. Eugene Stanley & Shlomo Havlin, 2016. "Multiple tipping points and optimal repairing in interacting networks," Nature Communications, Nature, vol. 7(1), pages 1-10, April.
    2. David Heath & Sidney Resnick & Gennady Samorodnitsky, 1998. "Heavy Tails and Long Range Dependence in On/Off Processes and Associated Fluid Models," Mathematics of Operations Research, INFORMS, vol. 23(1), pages 145-165, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pierre Perron & Eduardo Zorita & Wen Cao & Clifford Hurvich & Philippe Soulier, 2017. "Drift in Transaction-Level Asset Price Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 769-790, September.
    2. Zhong, Jilong & Zhang, FengMing & Yang, Shunkun & Li, Daqing, 2019. "Restoration of interdependent network against cascading overload failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 884-891.
    3. Gangwal, Utkarsh & Singh, Mayank & Pandey, Pradumn Kumar & Kamboj, Deepak & Chatterjee, Samrat & Bhatia, Udit, 2022. "Identifying early-warning indicators of onset of sudden collapse in networked infrastructure systems against sequential disruptions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    4. Leipus, Remigijus & Paulauskas, Vygantas & Surgailis, Donatas, 2005. "Renewal regime switching and stable limit laws," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 299-327.
    5. Vu T. N. Anh & Nguyen T. T. Hien & Le V. Thanh & Vo T. H. Van, 2021. "The Marcinkiewicz–Zygmund-Type Strong Law of Large Numbers with General Normalizing Sequences," Journal of Theoretical Probability, Springer, vol. 34(1), pages 331-348, March.
    6. Thomas Mikosch & Gennady Samorodnitsky, 2007. "Scaling Limits for Cumulative Input Processes," Mathematics of Operations Research, INFORMS, vol. 32(4), pages 890-918, November.
    7. Debicki, Krzysztof, 1999. "A note on LDP for supremum of Gaussian processes over infinite horizon," Statistics & Probability Letters, Elsevier, vol. 44(3), pages 211-219, September.
    8. M. Çağlar, 2004. "A Long-Range Dependent Workload Model for Packet Data Traffic," Mathematics of Operations Research, INFORMS, vol. 29(1), pages 92-105, February.
    9. Bernardo D’Auria & Gennady Samorodnitsky, 2005. "Limit Behavior of Fluid Queues and Networks," Operations Research, INFORMS, vol. 53(6), pages 933-945, December.
    10. Duffy, Ken & King, Christopher & Malone, David, 2007. "Ambiguities in estimates of critical exponents for long-range dependent processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 43-52.
    11. Rohit Deo & Meng-Chen Hsieh & Clifford M. Hurvich & Philippe Soulier, 2007. "Long Memory in Nonlinear Processes," Papers 0706.1836, arXiv.org.
    12. Li, Ming & Zhao, Wei, 2012. "Quantitatively investigating the locally weak stationarity of modified multifractional Gaussian noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6268-6278.
    13. Li, Ming & Li, Jia-Yue, 2017. "Generalized Cauchy model of sea level fluctuations with long-range dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 309-335.
    14. Irena Vodenska & Hideaki Aoyama & Yoshi Fujiwara & Hiroshi Iyetomi & Yuta Arai, 2016. "Interdependencies and Causalities in Coupled Financial Networks," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-32, March.
    15. Sidney Resnick & Gennady Samorodnitsky, 2000. "A Heavy Traffic Approximation for Workload Processes with Heavy Tailed Service Requirements," Management Science, INFORMS, vol. 46(9), pages 1236-1248, September.
    16. Michael M. Danziger & Albert-László Barabási, 2022. "Recovery coupling in multilayer networks," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    17. Wang, Shuliang & Gu, Xifeng & Luan, Shengyang & Zhao, Mingwei, 2021. "Resilience analysis of interdependent critical infrastructure systems considering deep learning and network theory," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:12:p:1396-:d:576039. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.