Release:Releases Archive. Вестник ТюмГУ. Физико-математические науки. Информатика (№7, 2014)
About the authors:Andrey S. Bezrukov, Post-graduate student, Department of Software Development, Institute of Mathematics and Computer Sciences, Tyumen State University
Abstract:The paper considers a method of representation of heterogeneous objects in the comparable indicators system to rank complexity comparable objects using subject domain rules defined in the form of dependency or algorithmically. It is described the subject area of sports management, problems in the efficiency calculation of sports facilities use. The performance indicators are determined. The model of homogeneous performance indicators is studied. Subject area's inconsistencies are identified. Characteristics of heterogeneous objects are explored. The results are approbated on the real data. It is proposed a model of an inhomogeneous system which allows to obtain adequate representation of objects for further processing, analysis, forecasting in artificial neural networks. The results can be used to simulate the performance of domain objects that differ in purpose or specifications as well for further development of models of homogeneous systems.
1. Bezrukov, A. S., Koynov, I. M. (2011) Accounting information system of sports facilities and contingent constantly involved in sports in Tyumen Region (in Russian). Best final qualifying works of graduates in 2011: collection of articles based on the best final qualifying works. Part 1. Science. p. 59–69.
2. On approval of statistical tools for the Russian Ministry of Sports to arrange federal statistical supervision of institutions of physical culture and sport. (23.10.2012 N 562).
3. Kaplan, R. S., Norton, D. P. (2006) Balanced scorecard. From strategy to action. Translated from the English by M. Pavlova. Moscow: Olimp-Business ZAO.
4. NedoSekin, A. O. (2004) Balanced scorecard: pros, cons, problems of implementation
(in Russian). Management XXI. 12. p. 35–48.
5. Jensen, M. C. (2001) Value maximization, stakeholder theory, and the corporate objective function. European Financial Management Review. [Online] 7. p. 297–317. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=220671. [Accessed: 4th March 2014].
6. Niven, P. R. (2006) Balanced scorecard diagnostics. Translated from the English by
V. O. Shagoyan. Moscow: Balance Business Books.
7. Shcherbakov, M. V. (2010) Specificity of application of intelligent data analysis models for energy efficiency (in Russian). Proceedings of Volgograd State Technical University. Series: Actual problems of management, computer science and informatics in technical systems.
9 (11). p. 72–76.
8. Karminskaya, T. D., Kovalev, V. Z., Tsyporin, P. I. (2011) Mathematical model of quality assessment activities of homogeneous objects ( in Russian). Proceedings of Tomsk State University of Control Systems and Radio electronics. 2 (24). p. 181–184.
9. Bezrukov, A. S. (2013) Application of artificial neural networks to predict the dynamics of the control object (the case study of sports facilities) (in Russian). Mathematical and information modeling: collection of scientific papers. 13. p. 49–54.