Mathematical model of political party competition
DOI:
https://doi.org/10.52575/2687-0932-2021-48-2-341-349Keywords:
events, system of differential equations, agitability coefficients, retirement coefficients, operator system, original, imageAbstract
One of the most important problems of social development is the organization of competition (struggle) of political parties. For the analysis and forecasting of this process, the most convenient method is mathematical modeling. The relevance of the development of a model of the struggle of parties is determined by the importance of the process under consideration for determining the strategy of the life of countries and peoples. In this study, a modified Richardson model (arms race) in the form of a dynamic system of differential equations is used to describe the competition of parties. An analytical solution of a dynamic system of differential equations is obtained using the operator method. To explain the developed method, a specific numerical example is considered. The features of the application of the model of competition of political parties are analyzed. The prospects for further development of the new developed method are determined. The developed method can be used for the analysis of interethnic, religious conflicts, for determining the maturation of an explosive, crisis situation in society. It allows you to analyze the clash of views and interests of individuals.
Downloads
References
Андрианова Е.Г., Головин С.А., Зыков С.В., Лесько С.А., Чукалина Е.Р. 2020. Обзор современных моделей и методов анализа временных рядов динамики процессов в социальных, экономических и социотехнических системах. Российский технологический журнал, 8 (4): 7–45. DOI https://doi.org/10.32362/2500-316X-2020-8-4-7-45.
Гильманов В.В. 2017. Партийные модели рекрутирования правящих элит и лидеров. Научные ведомости Белгородского государственного университета. Серия: История. Политология, 22 (271): 189–199.
Канищева О.И. 2017. Применение математических средств при моделировании военных конфликтов. Актуальные направления научных исследований XXI века: теория и практика, 8–1 (34–1): 200–204.
Михайлов А.П., Петров А.П., Прончева О.Г., Маревцева Н.А. 2017. Модель информационного противоборства в социуме при периодическом дестабилизирующем воздействии. Математическое моделирование, 29 (2): 23–32.
Остапенко В.В., Остапенко О.С., Беляева Е.Н., Ступницкая Ю.В. 2012. Математические модели борьбы партий за электорат или компаний за рынки сбыта. Кибернетика и системный анализ, 48 (6): 11–19.
Петров А.П., Прончева О.Г. 2019. Моделирование выбора позиций индивидами при информационном противоборстве с двухкомпонентной повесткой. Математическое моделирование, 31 (7): 91–108.
Петров А.П., Маслов А.И., Цаплин Н.А. 2015. Моделирование выбора позиций индивидами при информационном противоборстве в социуме. Математическое моделирование, 27 (12): 137–148.
Руренко Е.Н. 2017. Модель Ричардсона с управлением в одном частном случае. Advanced Science, 3: 123–129.
Сидоров В.В. 2016. Коалиционная политика политических партий в парламентских системах. Казань: Казан. ун-т, 149.
Фирсова И., Глухова Е. 2015. Математическая модель отношений между двумя государствами для решения проблем вооруженного конфликта. Финансовая жизнь, 1: 25–28.
Comissiong D.M.G., Sooknanan J. 2018. A review of the use of optimal control in social models. Internat. J. of Dynamics and Control, 6 (4): 1841–1846.
Dominioni G., Marasco A., Romano A. 2018. A mathematical approach to study and forecast racial groups interactions: deterministic modeling and scenario method, 52: 1929–1956. DOI doi.org/10.1007/s11135-017-0581-9.
Kubiv S. Balanyuk Y.Copyright, Kubiv S., Balanyuk Y. 2020. Development of a mathematical model of conflict between the parties in the implementation of the offset transaction. Technology audit and production reserves, Socionet; Technology audit and production reserves, 2(4(52)): 28–31. DOI 10.15587/2312-8372.2020.201260.
Marevtseva N.A. 2017. Model’ informatsionnogo protivoborstva v sotsiume pri periodicheskom destabiliziruyushchem vozdeistvii. Matematicheskoe modelirovanie, 29 (2): 23–32.
Misra А.К., Kumar A. 2012. A simple mathematical model for the spread of two political parties. Nonlinear Analysis: Modelling and Control, 17(3): 343–354.
Nyabadza F., Alassey T.Y., Muchatibaya G. 2016. Modelling the dynamics of two political parties in the presence of switching. SpringerPlus, 5: 1018. DOI https://doi.org/10.1186/s40064-016-2483-z.
Petukhov A.Yu., Malkhanov A.O., Sandalov V.M., Petukhov Yu.V. 2018. Modeling conflict in a social system using diffusion equations Simulation, 94 (12): 1053–1061. DOI https://doi.org/10.1177/0037549718761573.
Rinaldi S., Della Rossa F. 2018. Conflicts among N armed groups: scenarios from a new descriptive model. Nonlinear Dynamics, 92 (3): 3–12. DOI doi.org/10.1007/s11071-017-3446-9.
Tsybulin V.G., Khosaeva Z.K. 2019. Mathematical model of political differentiation under social tension. Computer Research and Modeling, 11 (5): 999-1012. DOI10.20537/2076-7633-2019-11-5-999-1012.
Winkel B. 2017. 2012-Misra-Mathematics Model for the Spread of Two Political Parties. https://www.simiode.org/resources/4091.
Abstract views: 370
Share
Published
How to Cite
Issue
Section
Copyright (c) 2021 ECONOMICS. INFORMATION TECHNOLOGIES
This work is licensed under a Creative Commons Attribution 4.0 International License.