DOI: 10.17586/2226-1494-2018-18-3-521-528


SHORTCUT ANALYTICAL-STATISTICAL MODELING METHODS FOR TECHNICAL SYSTEMS WITH DISTRIBUTED STRUCTURE

O. I. Kutuzov, T. M. Tatarnikova


Read the full article 
Article in Russian

For citation: Kutuzov O.I., Tatarnikova T.M. Shortcut analytical-statistical modeling methods for technical systems with distributed structure. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2018, vol. 18, no. 3, pp. 521–528 (in Russian). doi: 10.17586/2226-1494-2018-18-3-521-528

Abstract
 Subject of Research. The paper proposes a combined application of analytical-statistical modeling methods that makes it possible to accelerate the numerical calculation and analysis of the complex technical system characteristics by the method of machine simulation. The efficiency of joint application of analytical-statistical modeling methods was compared with direct modeling according to the number of tests. Methods. The layered modeling method gives the possibility to reduce the variance of the average characteristic estimation in comparison with the direct modeling method. The balanced modeling method enables a substantial reduction in the tests number without calculation accuracy loss. The joint application of analytical and statistical methods provides characteristics analysis acceleration for the systems  with a distributed structure by simulation method. Main Results. Interpretation and development of the stratification methods and balanced modeling are proposed with reference to system design problems. A test example is given demonstrating a possible gain in the application of analytical-statistical methods for simulation of unlikely events on the example of system reliability calculation. Practical Relevance.Joint application of the stratification methods and balanced modeling makes it possible to accelerate the algorithmic analysis of stochastic system models by the imitation method.

Keywords: Monte Carlo method, method convergence, analytical statistical modeling, experiments number, statistical experiment efficiency, statistical experiment acceleration, balanced modeling, layered modeling method

References
  1. Sovetov B.Ya., Yakovlev S.A. Modeling of Systems. Moscow, Vysshaya Shkola Publ., 2007, 343 p. (In Russian)
  2. Kutuzov O.I., Tatarnikova T.M. Practical Experience of Using Monte Carlo Method. Industrial Laboratory, 2017, vol. 83, no. 3, pp. 65–70. (In Russian)
  3. Sobol' I.M. Numerical Monte Carlo Methods. Moscow, Nauka Publ., 1973, 212 p. (in Russian)
  4. Pollyak Yu.G., Filimonov V.A. Statistical Machine Modeling of Communication Tools. Moscow, Radio i Svyaz' Publ., 1988, 176 p. (in Russian)
  5. Kutuzov O.I., Tatarnikova T.M. Mathematical Schemes and Algorithms of Infocommunication Systems Modeling. St. Petersburg, SUAI Publ., 2013, 148 p. (in Russian)
  6. Zadorozhnyi V.N., Kutuzov O.I. Problems and techniques for fractal queues modeling. Proc. Simulation Modeling: Theory and Practice. Kazan', Russia, 2013, pp. 143–148. (in Russian)
  7. Banks J., Carson J.S., Nelson B.L., Nicol D.M. Discrete-Event System Simulation. 5th ed. Prentice Hall, 2009, 638 p.
  8. Crane M.A., Lemoine A.J. An Introduction to the Regenerative Method for Simulation Analysis. Berlin, 1977.
  9. Bogatyrev V.A., Vinokurova M.S. Control and safety of operation of duplicated computer systems. Communications in Computer and Information Science, 2017, vol. 700, pp. 331–342. doi: 10.1007/978-3-319-66836-9_28
  10. Kleijnen J.P.C. Statistical Techniques in Simulation. Prentice-Hall, 1974.
  11. Kolchin V.F. Random Graphs. Moscow, Fizmatlit Publ., 2004, 256 p. (in Russian)
  12. Plaks B.I. Calculation of the reliability of systems with a complex structure by the accelerated Monte Carlo method. Izv. AN SSSR. Tekhn. Kibernetika, 1983, no. 6, pp. 158–162. (in Russian)
  13. Pugachev V.N. Combined Methods for Determining Probabilistic Characteristics. Moscow, Sovetskoe Radio Publ., 1973, 256 p. (in Russian)
  14. Zadorozhnyi V.N., Kutuzov O.I. Methods for Queues Simulating under Fractal Traffic in Packet Switched Networks. Omsk, OmSTU Publ., 2013, 104 p. (in Russian)
  15. Galambos Y. The Asymptotic Theory of Extreme Order Statistics. NY, Wiley, 1975.
  16. Bogatyrev V.A., Parshutina S.A. Multipath fault-tolerant routing models for distributing queries through the network. Herald of Computer and Information Technologies, 2015, no. 12, pp. 23–28. (in Russian)
  17. Christofides N. Graph Theory: An Algorithmic Approach. NY, Acadimic, 1975.


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Copyright 2001-2019 ©
Scientific and Technical Journal
of Information Technologies, Mechanics and Optics.
All rights reserved.

Яндекс.Метрика