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Modelling of threshold effects in the information processes of social systems
Petukhov Aleksandr

PhD in Politics

Director, Scientific Research Laboratory “Modelling of Social and Political Processes; Docent, the department of History and Theory of International Relations, N. I. Lobachevsky Nizhny Novgorod State University

603950,, Russia, g. Nizhnii Novgorod, ul. Pr.gagarina, 23



This work is dedicated to the problems of modelling and forecasting of information processes in the social systems, particularly the threshold effects in their dynamics. The indicated occurrences have the definitive impact upon the state of the system; however, the classical statistical models are not capable of forecasting them. It is demonstrated that the social system should be referred to multicomponent (i.e. consisting of large amount of elements) cognitive systems of distributed type (because the distance between separate elements plays a significant role from the standpoint of system activity). The basis of methodology lies in application of the methods of neural networks and approach to social systems as cognitive. The author suggests an approach towards the description of the dynamics of information processes and their inner hierarchy, depending on the scale of impact upon the social system overall. The managing information processes are determined as major. The concept of the threshold effect for similar processes is introduced. The author develops a model representation on the examined occurrences leaning on the nonlinear dynamics and neural networks (perceptron).

Keywords: cognitive algorithms, social systems, threshold effects, nonlinear dynamics, persperton, Information Processes, MKD - systems, social conflicts, revolution, security



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This article written in Russian. You can find full text of article in Russian here .

Plotinskii Yu.M. Modeli sotsial'nykh protsessov: Uchebnoe posobie dlya vysshikh uchebnykh zavedenii. – M.: Logos, 2001.
Malkov S.Yu. Matematicheskoe modelirovanie istoricheskoi dinamiki. Podkhody i protsessy. / Red. M. G. Dmitriev-M.: RGSU. 2004
Romanovskii Yu.M., Stepanova N.V., Chernavskii D.S. Matematicheskaya biofizika.-M.: Nauka, 1984.
Melik-Gaikazyan I.V. Informatsionnye protsessy i real'nost'.-M.: Nauka, Fizmatlit, 1998.
Malinetskii G.G., Potapov A.B. Sovremennye problemy nelineinoi dinamiki. – M.: Editorial URSS, 2000.
Malinetskii G.G. Khaos, struktury, vychislitel'nyi eksperiment. Vvedenie v nelineinuyu dinamiku.-M.: Nauka, 1997.
Loskutov A.Yu., Mikhailov A.S. Vvedenie v sinergetiku.-M.: Nauka, 1990.
Mikhailov, A. P. Gorbatikov E. A., “Bazovaya model' duumvirata v sisteme «vlast'-obshchestvo»”, Matem. modelirovanie, 24:1 (2012), 33–45
Mikhailov A. P., Petrov A. P., “Povedencheskie gipotezy i matematicheskoe modelirovanie v gumanitarnykh naukakh”, Matem. modelirovanie, 23:6 (2011), 18–32
Perov E.V. MONITORING SOTsIAL''NOI KONFLIKTOGENNOSTI OBShchESTVA // Natsional'naya bezopasnost' / nota bene. 2014. № 4. S. 574-583.
Petukhov A.Y. and Polevaya S.A. (2017). Modeling of cognitive brain activity through the Information Images Theory in terms of the bilingual Stroop test. International Journal of Biomathematics. Vol. 10, No. 6 (2017) 1750092 (16 pages) DOI: 10.1142/S1793524517500929
Miller, John; Page, Scott Complex Adaptive Systems. Princeton University Press. ISBN 978-0-691-12702-6
Khaken G. Sinergetika. Ierarkhiya neustoichivostei v samoorganizuyushchikhsya sistemakh i ustroistvakh. – M.: Mir, 1985
Principles of Neurodynamic: Perceptrons and the Theory of Brain Mechanisms. — M.: Mir, 1965. — 480 s.
Gorban' A. N. Neiroinformatika: kto my, kuda my idem, kak put' nash izmerit' // Vychislitel'nye tekhnologii. — M.: Mashinostroenie. — 2000. — № 4. — S. 10—14
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