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


O. I. Kutuzov, T. M. Tatarnikova

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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

 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

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