The article discusses a kinematic model of a group pursuing a single target by the method of parallel approach. The model is based on the fact that pursuers try to stick to pre-designed trajectories. The pursuer’s trajectories have curvature constraints. The initial directions of the pursuers’ velocities are arbitrary, which changes the well-known method of the parallel approach. In our model, the goal is achieved by the pursuers simultaneously. This is due to the change in the lengths of the predicted trajectories by time synchronization to reach the target. The change in length occurs due to an increase in the radius of curvature in the initial section of the trajectory.

The article considers a problem of classification of text documents of a higher educational institution using machine learning methods such as the Bayes method, the k-nearest neighbors algorithm, the decision tree method, and the support-vector machines. The study is conducted on a set of documents of the Siberian State Automobile and Highway University, Omsk, using the Python programming language. Preliminary processing of documents for the study is carried out. All studied documents are divided into four classes namely the order, the instruction, the letter, and the notice of a vacant position.
The process of classification of documents of a higher educational institution is presented. A comparative analysis of the classification results of each machine learning method is carried out on such metrics as the correctness of the classification algorithm, accuracy, completeness, F-measure, and the running
time of the algorithm. As a result of the research, the author gives recommendations on the application of the considered methods for the classification of university documents. The author suggests using a combination of methods to optimize the operation of the documents classifier.

The analysis of the effectiveness of algorithms for identifying areas of snow occurrence and the accuracy of measuring the moisture content of snow cover by satellite radiometry is carried out. The method of complex range-finding for remote measurement of snow cover characteristics is considered. The analysis of the measurement error of snow thickness using pulse, phase, and frequency modulation of probing signals is performed. The data of experimental measurements of the characteristics of the snow surface of the river section from the helicopter are presented. The technical implementation of the means of an unmanned aerial vehicle carrying out a comprehensive survey of the earth in winter conditions is described.

The paper considers the process of distribution of communication sessions between spacecraft and earth stations in the form of activity diagrams. To implement the algorithm, an analysis of the business processes of the distribution of communication sessions when controlling spacecraft
between earth stations is made. The criteria for an optimal communication session are formed. The software implementation of the algorithms is performed in the Mathcad environment, which allows testing the obtained algorithms with a limited number of earth stations and spacecraft. For an adequate assessment of the obtained algorithm, additional validation is carried out in the AnyLogic simulation environment. The program results for the automated planning of communication sessions and the simulation model of the distribution of the session demonstrated the efficiency of the
developed algorithm.

The article continues the authors’ research in the field of building systems for automatic diagnostics conditions and dynamics of plant growth. New concepts of intelligent farming, where field conditions are controlled by autonomous systems, have now become widely used. Building such systems requires solving several problems related to digital image processing, such as detecting plants and identifying their condition. Therefore, the article studies the actual problem of constructing an automatic system for assessing the state and dynamics of plant growth. As the central component of the system under consideration, the authors propose to use the mathematical apparatus of convolutional neural networks. The article describes the architecture, training procedure, and testing of the neural network. The results of computer experiments are presented. The analysis of the work of convolutional neural networks shows the high efficiency of the proposed solution to the problem of assessing the state and growth dynamics of biological crops.

The article presents an optimization method for the formation of quantitative weights of objects (importance of criteria, priorities of alternatives) according to the original expert judgment matrix in multicriteria selection problems. Since the pairwise comparison matrix can be considered as some perturbation of the multiplicative matrix, the proposed method is based on the approximation of the original pairwise comparison matrix by a multiplicative matrix according to the matrix criterion of minimum distances between matrices. A comparative analysis of the effectiveness of the new method with the well-known method of the analytical hierarchy of T. Saaty is carried out according to the criterion of closeness to the original judgment matrix of multiplicative matrices, the elements of which are reconstructed from the found normalized elements of the weights of objects. On the example of solving the problem for weights forming of the importance of criteria, the accuracy of the approximate solution of the analytical hierarchy method is estimated. This method is mathematically substantiated and, due to its computational simplicity, can be recommended instead of T. Saaty's hierarchy analysis method in solving applied multicriteria problems.

The article discusses the results of experimental studies of the vibrational propagation of a propane-air flame in a long vertical pipe that is closed at one end. Methods for physical modeling of a tulip-shaped flame in a cylindrical pipe are proposed. These methods are associated with the response of the flame front to external influences and critical conditions for its propagation. An explanation of the physical mechanisms governing the formation of a tulip flame with longitudinal and transverse edges, gas oscillations, combustion instability, and vortex formation in the flame is given.

The paper builds a regression model of the influence of the US gross domestic product, as well as the number of data breaches and exposed records, on the damage from cybercrimes. The parameters of this model represent a compromise Pareto estimate in the problem of minimizing the vector loss function. In identifying the parameters of the model, the method of least squares and minimization of the vector loss function are used. To improve the adequacy of the model, a compo-site variable is used that summarizes indicators characterizing the stolen information. The US statis-tical data for 2005–2019 is used as an information base for the model.

The article considers the issue of testing and optimization of the automated analyzer of turbid media. The conducted factor experiments show that the accuracy of the proposed method of correlation spectroscopy of scattered light by analyzing a video file allows obtaining results within the permissible error. If the number of samples corresponding to the statistical accuracy and the quality of the survey are observed, the particle size is calculated correctly and corresponds to the results obtained by other methods.