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National Interests: Priorities and Security

A priori estimate and reduction of the risk of demographic challenge to the national security of Russia. Part Two. Forecast and mitigation of the demographic risk through modeling

Vol. 15, Iss. 5, MAY 2019

Received: 7 February 2019

Received in revised form: 25 February 2019

Accepted: 14 March 2019

Available online: 16 May 2019

Subject Heading: Priorities of Russia

JEL Classification: C13, C31, K30, Z28

Pages: 817–834


Belov P.G. Moscow Aviation Institute (National Research University) (MAI), Moscow, Russian Federation


Subject The research represents the qualitative and quantitative analysis of my models of origination and detrimental effect of a demographic challenge to the national security of Russia. The analysis intends to forecast and reduce the respective risk.
Objectives The research illustrates the constructive nature of a cross-disciplinary approach to the prior assessment of the risk and optimization of decisions for its mitigation by addressing the most significant assumptions on its origination and adverse effects identified through modeling.
Methods The research is based on the automated systems analysis (in terms of quality and quantity) of original logic-probability and mathematical models in order to predict the risk and ranks of factors, optimize strategies and recommendations for reducing the risk through methods of the decision theory.
Results The research shows it is reasonable and constructive to implement cross-disciplinary methods for studying dangerous social processes. The article proves the possibility of expressing the qualities and parameters through membership functions of linguistic variables and fuzzy sets. I assessed the demographic risk and the impact of certain factors, proposed strategies for reducing the risk and optimizing the input and methods for processing it.
Conclusions and Relevance To ensure its national protection and security, Russia should opt for a reasonable and sound consistent strategy implying the proposed and other scientific and technological recommendations.

Keywords: challenge, modeling, risk, damage


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