and Computational Methods

Rubric: "2.3.1. System analysis, management and information processing (technical sciences)"

doi: 10.18698/2309-3684-2021-3-88104

This work is devoted to the study and application of methods of intellectual analysis for the implementation of the scheme of the nowcasting of dangerous phenomena. In the course of the work, data sets were formed with differ in the methods of information processing for their preparation. For each set, a number of mathematical models were constructed for classifying cloud cells according to the degree of danger of tornadoes forming from them. The Python programming language has been chosen as the main development language. The work is of great practical importance in the field of forecasting weather events. Its novelty lies in the use of modern machine learning methodology, instead of the traditional approach to data extrapolation, widely used in various schemes of nowcasting.

Шершакова А.О., Пархоменко В.П. Методы интеллектуального анализа данных в модели наукастинга опасных явлений. Математическое моделирование и численные методы, 2021, № 3, с. 88–104.

doi: 10.18698/2309-3684-2023-1-112123

The study's aim is to predict main trends and create scenarios for the economic development of BRICS countries (Brazil, India, China, Russia, South Africa) and the USA. Regression autonomous macro models were built, as well as a model of trade between them. The autonomous submodels use Population, Fixed Capital, Gross Domestic Product and Gross Capital Formation as key indicators. Autoregressive equations describe the dynamics of these variables. The resulting system of equations allowed us to describe the historical dynamics of demographic and macroeconomic indicators from 1990 to 2015 and to do a forecast until 2030. In the trade submodel bilateral trade flows link with gross domestic products of the economies. The relationship is described by the power dependence of the export flow on the gross domestic product of both trading partners. Unlike gravity-type models, the regression equation parameters are assumed to be constant for each pair of trading partners over the entire predicted time interval. The calculations showed that the models satisfactorily describe the dynamics of monotonically changing indicators and therefore can be used as a simple tool for forecasting the national and regional economy.

Малинецкий Г.Г., Махов С.А. Динамика макроэкономических показателей и взаимной торговли стран БРИКС и США. Математическое моделирование и численные методы, 2023, No 1, с. 112–123.

doi: 10.18698/2309-3684-2022-4-114125

The work is devoted to methods for detecting long-term memory in financial time series. Using the method of analysis with the help of the original program code, a number of values of the real financial index S & P500 were studied, estimates of the Hurst index were obtained, and persistence was demonstrated. To solve the problem of predicting the future values of a series, the ARFIMA model is proposed, which is a generalization of the standard ARIMA model and involves the use of a fractional differentiation opera-tor. A two-stage algorithm for constructing a forecast for a series of logarithmic profits is presented and implemented. It is shown that the use of the ARFIMA model improves the quality of the forecast in comparison with ARIMA for all standard metrics.

Облакова Т.В., Касупович Э. Численное исследование персистентных временных рядов на основе модели ARFIMA. Математическое моделирование и численные методы, 2022, № 4, с. 114–125.

doi: 10.18698/2309-3684-2023-2-155163

Based on the method of dynamics of averages, a model of two parties confrontation has been developed taking into consideration the bringing up of reserves by one of the parties. It is established that timely supply of reserves can significantly affect the course of the process and its final result. It is also shown that the use of the reserve at the beginning of the action significantly increases the capabilities of a group.

Чуев В.Ю., Дубограй И.В. Моделировании противоборства двух сторон c учетом резервирования. Математическое моделирование и численные методы,2023, № 2, с. 155–163

doi: 10.18698/2309-3684-2021-4-103120

The article deals with the problem of classifying pixels of the radar image (RI). A locally homogeneous radar image model was used, in which the readings of each small area (local area) were considered to belong to only one class. The classification results of several real radar images by local areas are compared using the statistical criteria for the maximum a posteriori probability, Kolmogorov and Cramer-Mises-Smirnov. At the same time, in the case when the listed criteria made it difficult to classify a local area — when it hit the interface of the underlying surfaces, it was considered to be assigned to a special, boundary class, and its readings were processed using the grid method for separating mixtures of probability distributions. For each criterion, the classification accuracy was evaluated as the proportion of correctly classified pixels within the selected homogeneous areas. It has been established that in the case of significant interclass differences, the best classification accuracy is ensured by the use of the least powerful Kolmogorov criterion among nonparametric criteria. Also, using a real image as an example, it is shown that when the differences in the characteristics of objects of the same class are comparable to interclass differences, the highest classification accuracy is achieved when using the maximum a posteriori probability criterion. Such cases are typical for a wide class of classification problems, including those not related to image processing.

Достовалова А.М. Моделирование локально-однородных радиолокационных изображений при использовании различных статистических критериев. Математическое моделирование и численные методы, 2021, № 4, с. 103–120.

doi: 10.18698/2309-3684-2022-2-88101

In this paper, optimization of the flight of a low-mass satellite from Earth orbit to the orbit of Venus using ion engines is considered. The first flight to the planet took place in 1961 by the Soviet automatic interplanetary station "Venus-1", which passed 100,000 kilometers from Venus. In addition, in 1962, the American station "Mariner-2" was flown. The most recent spacecraft launched to the planet was the European Space Agency's Venus Express in 2005, which flew to Venus in 153 days. When solving the current problem, the following assumptions were made: an interorbital flight is considered without taking into account the attraction of the planets, and the orbits of the planets are considered circular and lying in the same plane. The angle between the tangential velocity of the spacecraft and the thrust direction was chosen as the control. Optimization of satellite control was carried out using the Pontryagin maximum principle. The resulting boundary value problem for a system of ordinary differential equations was solved by a numerical method — the targeting method. Newton's method was used to solve systems of nonlinear algebraic equations. The calculation program was written using the C++ programming language. As a result of the work, it was possible to minimize the flight time between orbits, thus the operability of the shooting method for solving optimization problems was shown.

Мозжорина Т.Ю., Закуражная Д.А. Моделирование и оптимизация управления полетом космического аппарата с орбиты Земли на орбиту Венеры с помощью ионных двигателей. Математическое моделирование и численные методы, 2022, № 2, с. 90–103