Methodology for Determining the Limit Values of National Security Indicators Using Artificial Intelligence Methods

Authors

DOI:

https://doi.org/10.34021/ve.2022.05.04(1)

Keywords:

national security, homeostatic plateau, safety indicators, limit values, distribution types, automatic classification, artificial intelligence

Abstract

Applying artificial intelligence methods, the paper frames the algorithm structure and software for the formalized determination of the type of distribution (automatic classification) of the probability density function and the vector of limit values by justifying theoretically security gradations and determining quantitatively security indicators. The methodological basis of the research is the applied systems theory, statistical analysis, and methods of artificial intelligence (cluster analysis). The study of the approaches applied showed the absence of a theoretical basis for determining security gradations and the absence of their theoretical quantitative justification. The theoretical basis for determining security gradations is the concept of an extended "homeostatic plateau", which connects three levels of security in both directions: optimal, crisis, and critical with spheres of positive, neutral and negative feedback. To determine the bifurcation points (vector of limit values), the “t-criterion” method is used, which consists in constructing the probability density function of a “benchmark” sample, determining whether it belongs to the type of distribution with the calculation of statistical characteristics (mathematical expectation, mean square deviation, and asymmetry coefficient) and formalized calculation of the vector of limit values for characteristic types of distribution (normal, lognormal, exponential). To solve the problem of recognising (automatic classifying) the type of distribution of probability density functions of security indicators, artificial intelligence methods are used, namely, a discriminant method from the class of cluster analysis methods using quantitative and qualitative metrics: Euclidean distance, Manhattan metric and recognition by characteristic features. To digitize the determination of the vector of safety indicators limit values, an algorithm structure and software in the C++ programming language (version 6) have been developed, which ensures full automation of all stages of the algorithm and the adequacy of recognising graphic digital data with a predetermined number of clusters (types of distribution). A distinctive feature of the proposed method of formalized determination of the security indicators limit values is a complete absence of subjectivity and complete mathematical formalization, which significantly increases the speed, quality and reliability of the results obtained when evaluating the level of sustainable development, economic security, national security or national stability, regardless of the level of a researcher's qualification.

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References

Araujo, J.B., e Melo, P.F.F.F., & Schirru, R. (2009). Safety Indicators as a Tool for Operational Safety Evaluation of Nuclear Power Plants. Retrieved from https://inis.iaea.org/collection/NCLCollectionStore/_Public/41/057/41057374.pdf

Blashfield, R. K., & Aldenderfer, M. S. (1988). The Methods and Problems of Cluster Analysis. In J.R. Nesselroade and R. B. Cattell (Eds.), Handbook of Multivariate Experimental Psychology. Perspectives on Individual Differences (pp. 447-473). Boston, MA: Springer. Retrieved from https://doi.org/10.1007/978-1-4613-0893-5_14

Bogachov, S., Kwilinski, A., Miethlich, B., Bartosova, V., & Gurnak, A. (2020). Artificial Intelligence Components and Fuzzy Regulators in Entrepreneurship Development. Entrepreneurship and Sustainability Issues, 8(2), 487–499. https://doi.org/10.9770/jesi.2020.8.2(29)

Bonabeau, E., Dorigo, M., & Theraulas, G. (1999). Swarm Intelligence: From Natural to Artificial Systems. Oxford, UK: Oxford University Press.

Butlin, J. (1987). Our common future. By World commission on environment and development. Journal of International Development, 1(2), 284-287.

Canny, J. (1986). A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(6), 679-698. https://doi.org/10.1109/TPAMI.1986.4767851

Coban, H. H., Lewicki, W., Sendek-Matysiak, E., Łosiewicz, Z., Drożdż, W., & Miśkiewicz, R. (2022). Electric Vehicles and Vehicle–Grid Interaction in the Turkish Electricity System. Energies, 15(21), 8218. https://doi.org/10.3390/en15218218

Daly, H., & Townsend, K. (Eds.). (1993). Appreciating our Earth. Economics, ecology, ethics. Cambridge, Massachusetts: The MIT Press.

Drozdz, W., Marszalek-Kawa, J., Miskiewicz, R., & Szczepanska-Waszczyna, K. (2020a). Digital Economy in the Comporary World. Torun: Wydawnictwo Adam Marszalek.

Drożdż, W., Szczerba, P., & Kruszyński, D. (2020b). Issues related to the development of electromobility from the point of view of Polish utilities. Polityka Energetyczna – Energy Policy Journal, 23(1), 49-64. https://doi.org/10.33223/epj/119074

Dzwigol, H., Dzwigol-Barosz, M., Miskiewicz, R., & Kwilinski, A. (2020). Manager Competency Assessment Model in the Conditions of Industry 4.0. Entrepreneurship and Sustainability Issues, 7(4), 2630–2644. https://doi.org/10.9770/jesi.2020.7.4(5)

Gigch, J.P.V. (1978). Applied General Systems Theory. 2nd Edition. London, UK: HarperCollins Publishers LLC.

Hartigan, J. A. (1975). Clustering Algorithms. New York: John Vviley & Sons.

Hu., R. & Winsch, D. (2005). Survey of Clustering Algorithms. IEEE Transactions on Neural Networks, 16(3), 645-678. https://doi.org/10.1109/TNN.2005.845141

Huang, A., Chao, Y., de la Mora Velasco, E., Bilgihan, A. & Wei, W. (2022). When artificial intelligence meets the hospitality and tourism industry: an assessment framework to inform theory and management. Journal of Hospitality and Tourism Insights, 5(5), 1080-1100. https://doi.org/10.1108/JHTI-01-2021-0021

Johannesburg Declaration on Sustainable Development. (2002). Retrieved from http://www.un.org/ru/documents/decl_conv/ declarations/decl_wssd.shtml

Kachinskyi, A.B. (2013). National Security Indicators: Determination and Application of Their Limit Values: Monograph. Kyiv, Ukraine: The National Institute for Strategic Studies.

Kazyutinsky, V.V., & Balashov, Y.V. (1989). The anthropic principle. Nature, 1, 23-32.

Kharazishvili, Y. M. (2019). Systemic Security of Sustainable Development: Assessment Tools, Reserves and Strategic Implementation Scenarios: Monograph. Kyiv, Ukraine: Institute of Industrial Economics, National Academy of Sciences of Ukraine.

Kharazishvili, Y., Kwilinski, A., Grishnova, O., & Dzwigol, H. (2020). Social safety of society for developing countries to meet sustainable development standards: Indicators, level, strategic benchmarks (with calculations based on the case study of Ukraine). Sustainability, 12(21), 8953. https://doi.org/10.3390/su12218953

Kharazishvili, Y., Kwilinski, A., Sukhodolia, O., Dzwigol, H., Bobro, D., & Kotowicz, J. (2021). The Systemic Approach for Estimating and Strategizing Energy Security: The Case of Ukraine. Energies, 14(8), 2126. https://doi.org/10.3390/en14082126

Kornieiev, S.V. (2016). Operational System of Artificial Intelligence: The Basic Definitions. Artificial Intelligence, 4(74), 7-14. [in Russian].

Kuzior, A., Kwilinski, A. (2022). Cognitive Technologies and Artificial Intelligence in Social Perception. Management Systems in Production Engineering, 30(2), 109-115. https://doi.org/10.2478/mspe-2022-0014

Kuzior, A., Kwilinski, A., & Hroznyi, I. (2021a). The Factorial-Reflexive Approach to Diagnosing the Executors’ and Contractors’ Attitude to Achieving the Objectives by Energy Supplying Companies. Energies, 14(9), 2572. https://doi.org/10.3390/en14092572

Kwilinski, A. (2018). Mechanism of modernization of industrial sphere of industrial enterprise in accordance with requirements of the information economy. Marketing and Management of Innovations, 4, 116-128. http://doi.org/10.21272/mmi.2018.4-11

Kwilinski, A. (2019). Implementation of blockchain technology in accounting sphere. Academy of Accounting and Financial Studies Journal, 23(2), 1-6.

Kwilinski, A., & Kuzior, A. (2020). Cognitive Technologies in the Management and Formation of Directions of the Priority Development of Industrial Enterprises. Management Systems in Production Engineering, 28(2), 133-138. http://doi.org/10.2478/mspe-2020-0020

Kwilinski, A., Dalevska, N., & Dementyev, V.V. (2022b). Metatheoretical Issues of the Evolution of the International Political Economy. Journal of Risk and Financial Management, 15(3), 124. https://doi.org/10.3390/jrfm15030124

Kwilinski, A., Dielini, M., Mazuryk, O., Filippov, V., & Kitseliuk, V. (2020b). System Constructs for the Investment Security of a Country. Journal of Security and Sustainability Issues, 10(1), 345–358.

Kwilinski, A., Litvin, V., Kamchatova, E., Polusmiak, J., & Mironova, D. (2021). Information Support of the Entrepreneurship Model Complex with the Application of Cloud Technologies. International Journal of Entrepreneurship, 25(1), 1–8.

Kwiliński, A., Polcyn, J., Pająk, K., & Stępień, S. (2021). Implementation of Cognitive Technologies in the Process of Joint Project Activities: Methodological Aspect. In Conference Proceedings - VIII International Scientific Conference Determinants of Regional Development (pp. 96-126). Pila, Poland: Stanislaw Staszic University of Applied Sciences in Piła. https://doi.org/10.14595/CP/02/006

Kwilinski, A., Tkachenko, V., & Kuzior, A. (2019b). Transparent Cognitive Technologies to Ensure Sustainable Society Development. Journal of Security and Sustainability Issues, 9(2), 561–570.

LeCun, Y., Bengio, Y. & Hinton, G. (2015). Deep learning, Nature, 521, 436–444. https://doi.org/10.1038/nature14539

Lyulyov, O., Chortok, Y., Pimonenko, T., & Borovik, O. (2015). Ecological and economic evaluation of transport system functioning according to the territory sustainable development. International Journal of Ecology and Development, 30(3), 1-10.

Lyulyov, O., Vakulenko, I., Pimonenko, T., Kwilinski, A., Dzwigol, H., & Dzwigol-Barosz, M. (2021a). Comprehensive assessment of smart grids: Is there a universal approach? Energies, 14(12) https://doi.org/10.3390/en14123497

Lyulyov, O., Pimonenko, T., Kwilinski, A., & Us, Y. (2021b). The heterogeneous effect of democracy, economic and political globalisation on renewable energy. Paper presented at the E3S Web of Conferences, 250, 3006. https://doi.org/10.1051/e3sconf/202125003006

Melnychenko, O. (2020). Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security? Journal of Risk and Financial Management, 13, 191. https://doi.org/10.3390/jrfm13090191

Melnyk, L., Sineviciene, L., Lyulyov, O., Pimonenko, T., & Dehtyarova, I. (2018). Fiscal decentralization and macroeconomic stability: The experience of ukraine's economy. Problems and Perspectives in Management, 16(1), 105-114. https://doi.org/10.21511/ppm.16(1).2018.10

Ministry of Economic Development and Trade of Ukraine. (2013). On Approval of the Methodological Recommendations for Calculating the Level of Economic Security of Ukraine: Order of the President of Ukraine No. 1277 of 29.10.2013. Retrieved from https://zakon.rada.gov.ua/rada/show/v1277731-13#Text [in Ukrainian].

Miśkiewicz, R. (2018). The importance of knowledge transfer on the energy market. Polityka Energetyczna, 21(2), 49–62. https://doi.org/10.24425/122774

Miśkiewicz, R. (2021a). The Impact of Innovation and Information Technology on Greenhouse Gas Emissions: A Case of the Visegrád Countries. Journal of Risk and Financial Management, 14, 59. https://doi.org/10.3390/jrfm14020059

Miśkiewicz, R. (2021b). Knowledge and innovation 4.0 in today's electromobility. In Z. Makieła, M. M. Stuss, R. Borowiecki (Eds.), Sustainability, Technology and Innovation 4.0 (pp. 256-275). London, UK: Routledge.

Miskiewicz, R. (2022). Clean and Affordable Energy within Sustainable Development Goals: The Role of Governance Digitalization. Energies, 15(24), 9571. https://doi.org/10.3390/en15249571

Miśkiewicz, R., Matan, K., & Karnowski, J. (2022). The Role of Crypto Trading in the Economy, Renewable Energy Consumption and Ecological Degradation. Energies, 15(10), 3805. https://doi.org/10.3390/en15103805

Miśkiewicz, R., Rzepka, A., Borowiecki, R., & Olesińki, Z. (2021). Energy Efficiency in the Industry 4.0 Era: Attributes of Teal Organisations. Energies, 14(20), 6776. https://doi.org/10.3390/en14206776

Nilsson, N. J. (2009). The Quest for Artificial Intelligence. Cambridge, UK: Cambridge University Press.

Petroye, O., Lyulyov, O., Lytvynchuk, I., Paida, Y., & Pakhomov, V. (2020). Effects of information security and innovations on Country’s image: Governance aspect. International Journal of Safety and Security Engineering, 10(4), 459-466. https://doi.org/10.18280/ijsse.100404

Pimonenko, T., Lyulyov, O., & Us, Y. (2021). Cointegration between economic, ecological and tourism development. Journal of Tourism and Services, 12(23), 169-180. https://doi.org/10.29036/JOTS.V12I23.293

Reiman, T., & Pietikäinen. E. (2010). Indicators of safety culture – selection and utilization of leading safety performance indicators. Retrieved from https://www.stralsakerhetsmyndigheten.se/en/publications/reports/safety-at-nuclear-power-plants/2010/201007/

Russell, S., & Norvig, P. (2009). Artificial Intelligence: A Modern Approach (3rd Edition). New Jersey, Prentice Hall.

Saługa, P.W., Szczepańska-Woszczyna, K., Miśkiewicz, R., & Chład, M. (2020). Cost of equity of coal-fired power generation projects in Poland: Its importance for the management of decision-making process. Energies, 13(18), 4833. https://doi.org/10.3390/en13184833

Schmidhuber, J. (2015). Deep learning in neural networks: An overview. Neural Networks, 61, 85-117. https://doi.org/10.1016/j.neunet.2014.09.003.

Shafait, Z., Khan, M.A., Sahibzada, U.F., Dacko-Pikiewicz, Z., Popp, J. (2021). An assessment of students’ emotional intelligence, learning outcomes, and academic efficacy: A correlational study in higher education. PLoS ONE, 16(8), e0255428. https://doi.org/10.1371/journal.pone.0255428

Standford University. (2016). One Hundred Year Study on Artificial Intelligence. Retrieved from https://ai100.stanford.edu/2016-report

State Statistics Service of Ukraine. (2003). On Approval of the Methodology for Calculating Integral Regional Indices of Economic Development. Retrieved from https://zakon.rada.gov.ua/rada/show/v0114202-03#Text [in Ukrainian].

Sturges, H. A. (1926). The choice of a class-interval. Journal of the American Statistical Association, 21, 65-66. https://doi.org/10.1080/01621459.1926.10502161

Szczepańska-Woszczyna, K., & Gatnar, S. (2022). Key Competences of Research and Development Project Managers in High Technology Sector. Forum Scientiae Oeconomia, 10(3), 107-130. https://doi.org/10.23762/FSO_VOL10_NO3_6

Tkachenko, V., Kwilinski, A., Klymchuk, M., & Tkachenko, I. (2019). The Economic-Mathematical Development of Buildings Construction Model Optimization on the Basis of Digital Economy. Management Systems in Production Engineering, 27(2), 119–123. https://doi.org/10.1515/mspe-2019-0020

Tryon, R. C. (1939). Cluster analysis. London, UK: Ann Arbor Edwards Bros.

Turner, J. C. (1970). Modern Applied Mathematics. Probability. Statistics. Operational Research. London, UK: English Universities Press.

UNDP. (2012). The future we want: outcome of the Conference on Sustainable Development, Rio de Janeiro, Brazil, 20-22 June 2012. Retrieved from https://www.undp.org/turkiye/publications/future-we-want-united-nations-conference-sustainable-development-rio20-rio-de-janeiro-brazil-20-22-june-2012-outcome-conference

van Kampen, J., van der Beek, D., & Groeneweg, J. (2014). The Value of Safety Indicators. SPE Economics and Management, 6(03), 131–140. https://doi.org/10.2118/164954-PA

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Published

2022-12-30

How to Cite

Kharazishvili, Y., & Kwilinski, A. (2022). Methodology for Determining the Limit Values of National Security Indicators Using Artificial Intelligence Methods. Virtual Economics, 5(4), 7–26. https://doi.org/10.34021/ve.2022.05.04(1)

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