System diagnostics of socio-economic processes
System analysis in medicine and biology
Methods and models of system analysis
Y.E. Danik, D.A. Devyatkin, M.G. Dmitriev, M.I. Suvorova Modelling of rational development of the Arctic using open information (on the example of the Murmansk region)
Dynamic systems
Y.E. Danik, D.A. Devyatkin, M.G. Dmitriev, M.I. Suvorova Modelling of rational development of the Arctic using open information (on the example of the Murmansk region)


The article describes an approach to the modeling of socio-ecological and economic processes in the Arctic and the support of decision making, which means the decision to invest in one or the other industry. Such an approach is based on the ideal point method in the space of criteria. Three criteria are introduced. They are related to the optimization of the dynamics of economic, social and environmental state variables. Absence of some structured data can be partly compensated for by automated processing of unstructured data. Model experiments were performed for the Murmansk region of the Russian Federation. Their results showed that the approach can be applied to forecasting the state of the economy, the natural environment and human resources.


sinvestment, development modelling, scenario, the Arctic, Murmansk region.

PP. 42-52.

DOI: 10.14357/20790279180405


1. Ignatieva O.V. 2010. Razrabotka kontseptual’noy modeli ustoychivogo razvitiya regiona (na materialakh Vostochno-Kazakhstanskoy oblasti) [Development of a conceptual model of sustainable development of the region (on materials of the East Kazakhstan region)] PhD thesis. Almaty: University “Turan”.
2. Cziraky D. et al. 2002. A multivariate methodology for modelling regional development in Croatia. Croatian International Relations Review, 8(26/27), pp.35-52.
3. Cziráky D. et al. 2006. Regional development assessment: A structural equation approach. European Journal of Operational Research, 174(1), pp.427-442.
4. Mashunin Yu.K., Mashunin I.A. 2014. Forecasting the development of regional economy on the basis of input – output tables. Economy of Region. № 2 (38). pp. 276-289.
5. Mashunin I.A. and Mashunin Yu.K. 2016. Organization of management, modeling and forecasting of development of economy of the region. Regional economics and management: electronic scientific journal. № 1 (45). pp. 29-58.
6. Gurman V.I. et al. 2014. Scenario calculations of regional development strategies. Bulletin of the Buryat State University. Economics and management. №. 1. pp. 60-73.
7. Gurman V.I. et al. 2016. Kontseptual’naya osnova razrabotki kompleksa sotsio-ekologoekonomicheskikh modeley regiona [Conceptual basis for the development of the complex of socioecological and economic models of the region]. Economics of nature management, (4), pp.44-52.
8. Gurman V.I. et al. 2016. Possibilities of mathematical models and methods application to study of regional sustainable development problems on the case of the Arctic zone Program Systems: Theory and Applications, 7 (2 (29)). pp. 105-125.
9. Tsybatov V.A. 2015. Strategic planning of regional development: methods, models, information technology Regional Economics: Theory and Practice. № 27 (402). С. 36-52.
10. Partridge M.D. and Rickman D.S. 2010. Computable general equilibrium (CGE) modelling for regional economic development analysis. Regional studies, 44(10), pp.1311-1328.
11. Allan G.J. et al. 2017. Computable General Equilibrium Modelling in Regional Science. In Regional Research Frontiers-Vol. 2 (pp. 59-78). Springer, Cham.
12. Taylor L. 2016. CGE applications in development economics. Journal of Policy Modeling, 38(3), pp.495-514.
13. Ciscar J.C. et al. 2012. The integration of PESETA sectoral economic impacts into the GEM-E3 Europe model: methodology and results. Climatic Change, 112(1), pp.127-142.
14. Akopov A.S. et al. 2016. Modelling the Regional Ecological-Economic System with the Mechanism of the Government Regulation for the Case-Study of the Republic of Armenia. Economics of Contemporary Russia. № 1 (72). pp.109-119.
15. Antrim C.L. 2007. Converting Competition to Collaboration: Creative Applications of Models in the Law of the Sea Negotiations. In Diplomacy Games (pp. 211-228). Springer, Berlin, Heidelberg.
16. Nyhart J.D. et al. 1978. A cost model of deep ocean mining and associated regulatory issues.
17. Rumm N., Ortner B. and Löw H. 2014. Approaches to integrate various technologies for policy modeling. In Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling (pp. 272-295). IGI Global.
18. Gritsenko D. and Efimova E. 2017. Policy environment analysis for Arctic seaport development: the case of Sabetta (Russia). Polar Geography, 40(3), pp.186-207.
19. Sankaranarayanan J. et al. 2009, November. Twitterstand: news in tweets. In Proceedings of the 17th acm sigspatial international conference on advances in geographic information systems(pp. 42-51). ACM.
20. Hogenboom F. 2014. Automated detection of financial events in news text (No. EPS-2014-326-LIS).
21. Osipov G.S. et al. 2016. The concept of the decision support system for international negotiations in the Arctic region. International Multidisciplinary Scientific GeoConference: SGEM: Surveying Geology & mining Ecology Management, 1, pp.461-467.
22. Ananyeva M.I. et al. 2018. Extraction of financial and economic information from texts in Russian Proceedings of the Institute for Systems Analysis of the Russian Academy of Sciences, 68 (1), pp. 23-30.
23. Osipov G. et al. 2013. March. Relationalsituational method for intelligent search and analysis of scientific publications. In Proceedings of the Integrating IR Technologies for Professional Search Workshop (pp. 57-64).
24. Nivre J. et al. 2007. MaltParser: A languageindependent system for data-driven dependency parsing. Natural Language Engineering, 13(2), pp.95-135.
25. Dyachenko P.V. et al. 2015. A deeply annotated corpus of Russian texts (SynTagRus): contemporary state of affairs. Proceedings of the V.V. Vinogradov Russian Language Institute, (6), pp.272-300.
26. Devyatkin D.A, Suvorov R.E. and Sochenkov I.V. 2013. A method for topic clustering for large science publication collections. Information Technologies and Computing Systems, (1), p.33.
27. Sokirko A.V. 2004. Morfologicheskiye moduli na sayte www. aot. ru [Morphological modules on the site]. In Proceedings of the conference “Dialogue-2004”.
28. Shelmanov A., Devyatkin D. 2017. Semantic Role Labeling with Neural Networks for Texts in Russian. Annual International Conference “Dialog”. (1), pp. 245-257.


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