Popkov Aleksei Yur'evich

Publications in Math-Net.Ru

1. Entropy-randomized estimation of nonlinear dynamical model parameters on observation of dependent process
   
   Chelyab. Fiz.-Mat. Zh., 9:1 (2024),  144–159
2. Estimating the Hölder exponents based on the $\epsilon$-complexity of continuous functions: an experimental analysis of the algorithm
   
   Avtomat. i Telemekh., 2023, no. 4,  19–34
3. Randomized machine learning algorithms to forecast the evolution of thermokarst lakes area in permafrost zones
   
   Avtomat. i Telemekh., 2023, no. 1,  98–120
4. Forecasting of COVID-19 dynamics in EU using randomized machine learning applied to dynamic models
   
   Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2022, no. 3,  67–78
5. Randomized machine learning and forecasting of nonlinear dynamic models applied to SIR epidemiological model
   
   Informatics and Automation, 21:4 (2022),  659–677
6. Randomized machine learning of nonlinear models with application to forecasting the development of an epidemic process
   
   Avtomat. i Telemekh., 2021, no. 6,  149–168
7. Entropy-randomized projection
   
   Avtomat. i Telemekh., 2021, no. 3,  149–168
8. Entropine-randomized forecasting of the evolution of the area of thermokarst lakes
   
   Chelyab. Fiz.-Mat. Zh., 6:3 (2021),  384–396
9. Forecasting development of COVID-19 epidemic in European Union using entropy-randomized approach
   
   Informatics and Automation, 20:5 (2021),  1010–1033
10. Elements of randomized forecasting and its application to daily electrical load prediction in a regional power system
    
    Avtomat. i Telemekh., 2020, no. 7,  148–172
11. Deterministic and randomized methods of entropy projection for dimensionality reduction problems
    
    Inform. Primen., 14:4 (2020),  47–54
12. Cross-entropy reduction of data matrix with restriction on information capacity of projectors and their norms
    
    Matem. Mod., 32:9 (2020),  35–52
13. Entropy dimension reduction method for randomized machine learning problems
    
    Avtomat. i Telemekh., 2018, no. 11,  106–122
14. A method of generating random vectors with a given probability density function
    
    Avtomat. i Telemekh., 2018, no. 9,  31–45
15. Iterative MC-algorithm to solve the global optimization problems
    
    Avtomat. i Telemekh., 2017, no. 2,  82–98
16. Monte Carlo method of batch iterations: probabilistic characteristics
    
    Avtomat. i Telemekh., 2015, no. 5,  60–71
17. Parallel implementation of the algorithm for solving entropy-robust estimation problem on heterogeneous computer systems
    
    Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2015, no. 4,  51–60
18. Parallel Monte Carlo for entropy-robust estimation
    
    Matem. Mod., 27:6 (2015),  14–32
19. Parametric and nonparametric estimation for characteristics of randomized models under limited data (entropy approach)
    
    Matem. Mod., 27:3 (2015),  63–85
20. Estimating the characteristics of randomized dynamic data models (the entropy-robust approach)
    
    Avtomat. i Telemekh., 2014, no. 5,  83–90
21. Method of Monte Carlo batch iteration to solving by global optimization problems
    
    Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2014, no. 3,  39–52
22. Estimation of characteristics of randomized static models of data (entropy-robust approach)
    
    Avtomat. i Telemekh., 2013, no. 11,  114–131
23. Entropy model of the investment portfolio
    
    Avtomat. i Telemekh., 2006, no. 9,  179–190
24. Gradient methods for nonstationary unconstrained optimization problems
    
    Avtomat. i Telemekh., 2005, no. 6,  38–46
25. Forced Oscillations in Systems with $Arg\min$ Type Operators
    
    Avtomat. i Telemekh., 2002, no. 11,  13–23
26. Multiplicative algorithms for reconstructing images from projections
    
    Avtomat. i Telemekh., 1998, no. 1,  60–77