Leonid A. Sevastyanov

dblp:19/10948 · also Leonid A. Sevast'yanov, Leonid A. Sevastianov · DBLP profile ↗
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9ranked-venue papers
2as first author
1since 2021 · last 2021
0000-0002-1856-4643ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 6 · 2 first-author · 1 since 2021Artificial intelligence and machine learning · 3
YearPublicationVenuePosition
2021 On symbolic integration of algebraic functions
Mikhail D. Malykh, Leonid A. Sevastyanov
J. Symb. Comput.2
2020 On Periodic Approximate Solutions of the Three-Body Problem Found by Conservative Difference Schemes
Edik A. Ayryan, Mikhail D. Malykh, Leonid A. Sevastyanov, Yu Ying
CASC3
2019 On Explicit Difference Schemes for Autonomous Systems of Differential Equations on Manifolds
Edik A. Ayryan, Mikhail D. Malykh, Leonid A. Sevastyanov, Yu Ying
CASC3
2019 Symbolic-Numeric Implementation of the Four Potential Method for Calculating Normal Modes: An Example of Square Electromagnetic Waveguide with Rectangular Insert
Anastasia A. Tiutiunnik, Dmitry V. Divakov, Mikhail D. Malykh, Leonid A. Sevastyanov
CASC4
2017 Approaches To Stochastic Modeling Of Wind Turbines
abstract
Background. This paper study statistical data gathered from wind turbines located on the territory of the Republic of Poland. The research is aimed to construct the stochastic model that predicts the change of wind speed with time. Purpose. The purpose of this work is to find the optimal distribution for the approximation of available statistical data on wind speed. Methods. We consider four distributions of a random variable: Log-Normal, Weibull, Gamma and Beta. In order to evaluate the parameters of distributions we use method of maximum likelihood. To assess the the results of approximation we use a quantile-quantile plot. Results. All the considered distributions properly approximate the available data. The Weibull distribution shows the best results for the extreme values of the wind speed. Conclusions. The results of the analysis are consistent with the common practice of using the Weibull distribution for wind speed modeling. In the future we plan to compare the results obtained with a much larger data set as well as to build a stochastic model of the evolution of the wind speed depending on time.
Migran N. Gevorkyan, Anastasiya V. Demidova, Ivan Zaryadov, Robert Adam Sobolewski, Anna V. Korolkova, Dmitry S. Kulyabov, Leonid A. Sevastyanov
ECMS7
2016 Stochastization Of One-Step Processes In The Occupations Number Representation
Anna V. Korolkova, Ekaterina G. Eferina, Eugeny B. Laneev, Irina A. Kochetkova, Leonid A. Sevastyanov, Dmitry S. Kulyabov
ECMS5
2016 Hybrid Simulation Of Active Traffic Management
Anna V. Korolkova, Tatiana R. Velieva, Pavel O. Abaev, Leonid A. Sevastyanov, Dmitry S. Kulyabov
ECMS4
2014 Analytical Calculations in Maple to Implement the Method of Adiabatic Modes for Modelling Smoothly Irregular Integrated Optical Waveguide Structures
Leonid A. Sevastyanov, Anton L. Sevastyanov, Anastasia A. Tiutiunnik
CASC1
2013 A Quantum Measurements Model of Hydrogen-Like Atoms in Maple
Leonid A. Sevastyanov, Alexander V. Zorin, Alexander Gorbachev
CASC1