Design features of the information technology for the labor migrants group structure determination

Authors

DOI:

https://doi.org/10.15587/1729-4061.2015.47204

Keywords:

labor migrants group structure determination, fuzzy c-means method, information technology

Abstract

The necessity of solving poorly structured and unstructured tasks in dealing with complex scientific and technical problems causes the need for developing relevant models, methods, and software. The task of the labor migrants group structure determination is faced by experts in the field of HIV/AIDS prevention and treatment in the process of investigating behavioral risks of the target group representatives.

In the paper, the verbal and mathematical formulation of the labor migrants group structure determination problem as the fuzzy clustering problem based on the assumption of a simultaneous object belonging to different clusters was performed. To solve the problem, it was proposed to use the adapted fuzzy c-means method based on the representation of non-numeric values by linguistic variables. This has allowed to find the distance between objects, the attribute vectors of which have both numeric and non-numeric components.

The design features of the information-analytical system for solving tasks were determined. The system of tasks that must be implemented in the information-analytical system was defined, grouping of mathematical models and methods that form the basis of an analytical system unit was performed. The structural-functional diagram of the relevant information-analytical system was developed.

Experimental verification of research results on the example of solving the problem of people grouping according to the labor migration direction has confirmed the efficiency of the developed technology and the possibility of its use to improve the decision making efficiency in the field of HIV/AIDS prevention and treatment in the study of behavioral risks of the target group representatives.

Author Biography

Оксана Юріївна Мулеса, Uzhgorod national university, Narodna 3, Uzhgorod, Ukraine, 88000

Candidate of Technical Science, Associate Professor

Department of cybernetics and applied mathematics

References

  1. Myronyuk, I. S. (2012). Behavioral risk of HIV infection related to labor migration. Preventive Medicine, № 2 (18), 7–10.
  2. UNAIDS. (2002). Focus: AIDS and mobile populations. Report on the global HIV/AIDS epidemic, 117–123.
  3. Bobrik, A. V., Eroshina, K. M., Michel, E. A. (2009). Organization of comprehensive HIV prevention, STD and viral hepatitis among migrant workers. Moscow, 32.
  4. Myronyuk, I. S. (2012). Features risk behaviors of HIV-positive migrants Transcarpathian region by region Migration. Scientific Bulletin of the Uzhgorod University, The series "Medicine", 1 (43), 146–151.
  5. Mulesa, O. (2013). Consecutive analysis of variations in fuzzy clustering and identification tasks. Bulletin of Kyiv National Taras Shevchenko University, Series of Physical-Mathematical Sciences, 2, 205–209.
  6. Mulesa, O. (2013). Technology of quantitative evaluation of high risk groups of infection with human immunodeficiency virus under uncertainty. Proceedings of the National Technical University "KPI", Series: "New solutions in modern technologies", 56 (1029), 172–179.
  7. Baturkin, S. A., Baturkina, E. Yu., Zimenko, V. A., Sihinov, Y. V. (2010). Statistical data clustering algorithms in adaptive learning systems. Vestnyk RHRTU, 1 (31), 82–85.
  8. Kotov, A., Krasylnykov, N. (2012). Data clustering. Available: yury.name/internet/02ia-seminar-note.pdf
  9. Horbachenko, V. Y. (1013). Networks and Kohonen maps. Available: http://gorbachenko.self-organization.ru/index.html
  10. Snytiuk, V. (2005). Evolutionary clustering of complex objects and processes. XI-th International Conference «Knowledge-Dialogue-Solution», Varna, Vol. 1, 232–237.
  11. Grop, D. (1979). Methods of identification systems. Moscow: Mir, 302.
  12. Nakonechny, S., Tereshchenko, T, Romaniuk, T. (2004). Econometrics. Kyiv: KNEU, 520.
  13. Mulesa, O. (2015). Adaptation of fuzzy c-means method for determination the structure of social groups. Technology Audit And Production Reserves, 2(2(22)), 73-76. doi:10.15587/2312-8372.2015.41014
  14. Voloshyn, O. F., Mashchenko, S. O. (2010). Decision theory. Kiev: Publishing and Printing Center "Kyivskyi universytet", 366.
  15. Orlovskyi, S. A. (1981). Decision making with fuzzy initial information. Moscow: Nauka. Hlavnaia redaktsyia fyzyko-matematycheskoi lyteratury, 208.

Published

2015-08-25

How to Cite

Мулеса, О. Ю. (2015). Design features of the information technology for the labor migrants group structure determination. Eastern-European Journal of Enterprise Technologies, 4(2(76), 4–8. https://doi.org/10.15587/1729-4061.2015.47204