Gorshenin Andrey Konstantinovich

Publications in Math-Net.Ru

1. MMRFIGN: an ensemble graph segmentation model for imbalanced high-resolution images informed by multicomponent Markov random fields
   
   Dokl. RAN. Math. Inf. Proc. Upr., 527 (2025),  156–170
2. Neural network image classifiers informed by factor analyzers
   
   Dokl. RAN. Math. Inf. Proc. Upr., 520:2 (2024),  41–48
3. Toward clustering of network computing infrastructure objects based on analysis of statistical anomalies in network traffic
   
   Inform. Primen., 17:3 (2023),  76–87
4. Increasing FOREX trading profitability with LSTM candlestick pattern recognition and tick volume indicator
   
   Inform. Primen., 16:3 (2022),  26–38
5. Method for improving accuracy of neural network forecasts based on probability mixture models and its implementation as a digital service
   
   Inform. Primen., 15:3 (2021),  63–74
6. On deep Gaussian mixture models in machine learning problems
   
   Intelligent systems. Theory and applications, 25:4 (2021),  121–124
7. On modeling trading strategies for currency pairs using deep neural networks and method of moving separation of mixtures
   
   Intelligent systems. Theory and applications, 25:4 (2021),  92–95
8. Statistical estimation of distributions of random coefficients in the Langevin stochastic differential equation
   
   Inform. Primen., 14:3 (2020),  3–12
9. Approximation of particle size distributions of lunar regolith based on the resampling
   
   Inform. Primen., 14:2 (2020),  50–57
10. Analysis of configurations of LSTM networks for medium-term vector forecasting
    
    Inform. Primen., 14:1 (2020),  10–16
11. Application of recurrent neural networks to forecasting the moments of finite normal mixtures
    
    Inform. Primen., 13:3 (2019),  114–121
12. Hybrid extreme gradient boosting models to impute the missing data in precipitation records
    
    Inform. Primen., 13:3 (2019),  34–40
13. Optimization of hyperparameters of neural networks using high-performance computing for prediction of precipitation
    
    Inform. Primen., 13:1 (2019),  75–81
14. Development of services of digital platforms to overcome nonfinancial barriers
    
    Inform. Primen., 12:4 (2018),  106–112
15. New mixture representations of the generalized Mittag-Leffler distribution and their applications
    
    Inform. Primen., 12:4 (2018),  75–85
16. Determining the extremes of precipitation volumes based on the modified “Peaks over Threshold” method
    
    Inform. Primen., 12:4 (2018),  16–24
17. Data noising by finite normal and gamma mixtures with application to the problem of rounded observations
    
    Inform. Primen., 12:3 (2018),  28–34
18. Forecasting moments of finite normal mixtures using feedforward neural networks
    
    Sistemy i Sredstva Inform., 28:3 (2018),  62–71
19. Pattern-based analysis of probabilistic and statistical characteristics of extreme precipitation
    
    Inform. Primen., 11:4 (2017),  38–46
20. On some mathematical and programming methods for construction of structural models of information flows
    
    Inform. Primen., 11:1 (2017),  58–68
21. Learning management system ELIS. User interface and functional capabilities
    
    Sistemy i Sredstva Inform., 27:2 (2017),  70–84
22. Learning management system ELIS. Architecture solutions
    
    Sistemy i Sredstva Inform., 27:2 (2017),  60–69
23. MSM Tools as a heterogeneous computing service
    
    Sistemy i Sredstva Inform., 27:1 (2017),  60–72
24. Analytical solution of the optimal control task of a semi-Markov process with finite set of states
    
    Inform. Primen., 10:4 (2016),  72–88
25. Development of the algorithm of numerical solution of the optimal investment control problem in the closed dynamical model of three-sector economy
    
    Inform. Primen., 10:1 (2016),  82–95
26. Concept of online service for stochastic modeling of real processes
    
    Inform. Primen., 10:1 (2016),  72–81
27. Application of the CUDA architecture for implementation of grid-based algorithms for the method of moving separation of mixtures
    
    Sistemy i Sredstva Inform., 26:4 (2016),  60–73
28. On a realization of an automated testing service
    
    Sistemy i Sredstva Inform., 26:1 (2016),  62–75
29. Statistical modeling of air–sea turbulent heat fluxes by the method of moving separation of finite normal mixtures
    
    Inform. Primen., 9:4 (2015),  3–13
30. A visualization of estimators in the method of moving separation of mixtures
    
    Inform. Primen., 8:4 (2014),  78–84
31. Information technology to research the fine structure of chaotic processes in plasma by the analysis of spectra
    
    Sistemy i Sredstva Inform., 24:1 (2014),  116–127
32. Parallelism in microprocessors
    
    Sistemy i Sredstva Inform., 24:1 (2014),  46–60
33. Probability and statistical modeling of information flows in complex financial systems based on high-frequency data
    
    Inform. Primen., 7:1 (2013),  12–21
34. On the investigation of plasma turbulence by the analysis of the spectra
    
    Computer Research and Modeling, 4:4 (2012),  793–802
35. On application of the asymptotic tests for estimating the number of mixture distribution components
    
    Computer Research and Modeling, 4:1 (2012),  45–53
36. On stability of normal location mixtures with respect to variations in mixing distribution
    
    Inform. Primen., 6:2 (2012),  22–28
37. Stability of normal scale mixtures with respect to variations in mixing distribution
    
    Sistemy i Sredstva Inform., 22:1 (2012),  167–179
38. An asymptotically optimal test for the number of components of a mixture of probability distributions
    
    Inform. Primen., 5:3 (2011),  4–16
39. The evolution of probability characteristics of low-frequency plasma turbulence
    
    Mat. Model., 23:5 (2011),  35–55
40. Analysis of fine stochastic structure of chaotic processes by kernel estimators
    
    Mat. Model., 23:4 (2011),  83–89
41. On convergence of SEM estimates sequence for statistical separation of mixture distribution
    
    Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2011, no. 23,  39–50
42. The robust version of EM-algorithm for finite normal mixtures
    
    Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2011, no. 22,  63–72
43. Median modification of EM- and SEM-algorithms for separation ofmixtures of probability distributions and their application to the decomposition of volatility of financial time series
    
    Inform. Primen., 2:4 (2008),  12–47