The role of artificial intelligence technologies in long-term socio-economic development and integrated security

Grinyaev, S. N.; Medvedev, Dmitry; Pravikov, Dmitriy I.; Samarin, I.V.; Silantyev, Albert U.

doi:10.21533/pen.v9i3.2109

Cited by 6 publications

(2 citation statements)

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“…from outside. The main characteristics of such threats are that they develop and spread in one area and have harmful effects in several other areas (Grinyaev et al, 2020).…”

Section: Strategic Processesmentioning

confidence: 99%

Evolution of Russian Strategic Planning in the Arctic and Enhancing of Integrated Security of the Fuel and Energy Complexes

Grinyaev,

Medvedev,

Zafar

2023

International Studies

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The Arctic region witnessed a lot of geopolitical activism and contestation during 2008 to 2020. These activities have had direct impact on the Arctic Policy of the Russian Federation. The present article analyses the changes in the Russian Arctic policy, including security policy and their evolution and development during this period of changed economic, political and strategic environment. To identify and appreciate the changes in the policy, a comparative analysis of the Russian strategic planning documents towards Arctic has been carried out. It reveals a transformation of approach that ensures economic development and security of critical energy facilities situated in the region. The study also analyses the achievement of the goals set by the ‘Basic Principles of Russian Federation State Policy in the Arctic to 2020’ adopted in 2008 and describes the conditions for achieving the strategic goals in the Russian Arctic zone.

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“…from outside. The main characteristics of such threats are that they develop and spread in one area and have harmful effects in several other areas (Grinyaev et al, 2020).…”

Section: Strategic Processesmentioning

confidence: 99%

Evolution of Russian Strategic Planning in the Arctic and Enhancing of Integrated Security of the Fuel and Energy Complexes

Grinyaev,

Medvedev,

Zafar

2023

International Studies

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“…To further examine the effects of related factors, the Back Propagation Neural Networks (BPNN) are adopted to predict independent variables (IV), such as the states (y 1 ), duration (y 2 ), number of alliances (y 3 ), number of wars (y 4 ). The dependent variables (Grinyaev et al, (2021)) include the bellicosity (x 1 ), the propensity of alliance (x 2 ), the betrayal threshold (x 3 ), the winner cost (x 4 ) & the loser cost (x 5 ). All related variables (x 1 , x 2 , x 3 , x 4 , & x 5 ) are regeared as five input neurons to construct the input layer of BP neural networks.…”

Section: History Knowledge Via Bp Neural Networkmentioning

confidence: 99%

Human civilization dynamics: why we have different civilization patterns in history

Lu,

Zhang,

Onyebuchi

et al. 2023

Humanit Soc Sci Commun

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After the Axial Age, the West moved toward continuous disunity, but China had successfully maintained a persistent unity pattern. Conventional case (history event) studies are subject to selection bias and theoretical frameworks, which is not objective narrative. We use agent-based modeling (ABM) to reveal the historical dynamics of why civilizations take on distinct patterns (unity versus disunity). In China, the Qin Dynasty (initial unity) opened the Great Unity tradition in 221 BC. Before this, there was a major chaotic period (770 BC to 221 BC) with two periods. The first period, the Spring and Autumn (770 BC to 221 BC), opened this chaotic process and indirectly led to the initial unity. Then, the second period, the Warring States period (475 BC to 221 BC), directly led to this initial unity. This work models the second period and focuses on the question of why human civilizations take on different patterns in history. Finally, we have solved the conditions and boundaries of two patterns. Based on the second period, we have different conclusions. The bellicosity threshold is around 0.2 (for the previous period, this is 0.3), and the alliance propensity threshold is around 0.8 (for the previous period, this is 0.7). Moreover, the higher winner cost (beyond 5%) makes it impossible to achieve Unity. This work has one new contribution, such as solving social knowledge. We use BP neural networks to evaluate the knowledge graph to support history learning. It explains civilization patterns for humankind.

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Mathematical Modeling of an Additional Shunt Zone in Track Circuits With a Potential Receiver: Algorithm and Calculations

Aliev,

Tohirov,

Aliev

2024

Intellectual Technologies on Transport

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The paper presents an algorithm and methodology for calculating the additional shunt zone in track circuits with a potential receiver. The issues of mathematical modeing of a seamless track circuit are considered, and a method is proposed for determining the maximum shunting zone when the train moves away from the track circuit. The calculation results make it possible to conduct research and determine the optimal parameters of rail circuits with a potential receiver, which is important for taking technical easures to improve the operation of transport systems.

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The role of artificial intelligence technologies in long-term socio-economic development and integrated security

Cited by 6 publications

References 0 publications

Evolution of Russian Strategic Planning in the Arctic and Enhancing of Integrated Security of the Fuel and Energy Complexes

Evolution of Russian Strategic Planning in the Arctic and Enhancing of Integrated Security of the Fuel and Energy Complexes

Human civilization dynamics: why we have different civilization patterns in history

Mathematical Modeling of an Additional Shunt Zone in Track Circuits With a Potential Receiver: Algorithm and Calculations

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