11 - 20 out of 48Page size: 10
  1. 2023

  2. Study of Superexponential Growth of the Mean Particle Flux by Monte Carlo Method

    Lotova, G. Z. & Mikhailov, G. A., Sept 2023, In: Numerical Analysis and Applications. 16, 3, p. 229-235 7 p.

    Research output: Contribution to journal › Article › peer-review

  3. Статистическое моделирование. Методы Монте-Карло

    Михайлов, Г. А. & Войтишек, А. В., 2023, Москва: Юрайт. 323 p. (Высшее образование)

    Research output: Book/Report › Teaching manual › peer-review

  4. 2022

  5. Estimation of the average particle flux in a stochastically homogeneous medium by Monte Carlo method

    Lotova, G. Z. & Mikhailov, G. A., 1 Dec 2022, In: Russian Journal of Numerical Analysis and Mathematical Modelling. 37, 6, p. 363-371 9 p.

    Research output: Contribution to journal › Article › peer-review

  6. Construction and optimization of numerically-statistical projection algorithms for solving integral equations

    Korda, A. S., Mikhailov, G. A. & Rogasinsky, S. V., 1 Aug 2022, In: Russian Journal of Numerical Analysis and Mathematical Modelling. 37, 4, p. 213-219 7 p.

    Research output: Contribution to journal › Article › peer-review

  7. Comparative Analysis of Numerical-Statistical Projection Algorithms for Solving Transfer Theory Problems

    Mikhailov, G. A., Korda, A. S. & Rogasinsky, S. V., Feb 2022, In: Doklady Mathematics. 105, 1, p. 35-38 4 p.

    Research output: Contribution to journal › Article › peer-review

  8. Construction of Effective Randomized Projective Estimates for Solutions of Integral Equations Based on Legendre Polynomials

    Mikhailov, G. A., Korda, A. S. & Rogasinsky, S. V., 2022, In: Doklady Mathematics. 106, 3, p. 475-478 4 p.

    Research output: Contribution to journal › Article › peer-review

  9. Статистическое моделирование. Методы Монте-Карло

    Михайлов, Г. А. & Войтишек, А. В., 2022, Москва: Юрайт. 323 p. (Высшее образование)

    Research output: Book/Report › Teaching manual › peer-review

  10. 2021

  11. International Conference «Marchuk Scientific Readings 2021» (MSR-2021)

    Mikhailov, G. A., Kabanikhin, S. I., Laevsky, Y. M., Penenko, V. V., Glinsky, B. M., Zagorulko, Y. A., Shishlenin, M. A., Podkolodnyy, N. L. & Penenko, A. V., 13 Dec 2021, In: Journal of Physics: Conference Series. 2099, 1, 011001.

    Research output: Contribution to journal › Editorial › peer-review

  12. Numerical-statistical study of the prognostic efficiency of the SEIR model

    Lotova, G. Z., Lukinov, V. L., Marchenko, M. A., Mikhailov, G. A. & Smirnov, D. D., 1 Dec 2021, In: Russian Journal of Numerical Analysis and Mathematical Modelling. 36, 6, p. 337-345 9 p.

    Research output: Contribution to journal › Article › peer-review

  13. New correlative randomized algorithms for statistical modelling of radiation transfer in stochastic medium

    Mikhailov, G. A. & Medvedev, I. N., 1 Aug 2021, In: Russian Journal of Numerical Analysis and Mathematical Modelling. 36, 4, p. 219-225 7 p.

    Research output: Contribution to journal › Article › peer-review

Previous 1 2 3 4 5 Next

ID: 3443097