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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 .

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