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Conjugate gradient algorithms represent an important class of unconstrained optimization algorithms with strong local and global convergence properties and simple memory requirements. These algorithms have advantages that place them between the steep regression method and Newton’s algorithm because they require calculating the first derivatives only and do not require calculating and storing the second derivatives that Newton’s algorithm needs. They are also faster than the steep descent algorithm, meaning that they have overcome the slow convergence of this algorithm, and it does not need to calculate the Hessian matrix or any of its approximations, so it is widely used in optimization applications. This study proposes a novel method for image restoration by fusing the convex combination method with the hybrid (CG) method to create a hybrid three-term (CG) algorithm. Combining the features of both the Fletcher and Revees (FR) conjugate parameter and the hybrid Fletcher and Revees (FR), we get the search direction conjugate parameter. The search direction is the result of concatenating the gradient direction, the previous search direction, and the gradient from the previous iteration. We have shown that the new algorithm possesses the properties of global convergence and descent when using an inexact search line, relying on the standard Wolfe conditions, and using some assumptions. To guarantee the effectiveness of the suggested algorithm and processing image restoration problems. The numerical results of the new algorithm show high efficiency and accuracy in image restoration and speed of convergence when used in image restoration problems compared to Fletcher and Revees (FR) and three-term Fletcher and Revees (TTFR).

This paper addresses the problem of the plane-parallel motion of an elliptic foil with an attached point vortex of constant strength in an ideal fluid. It is assumed that the position of the vortex relative to the foil remains unchanged during motion. The flow of the fluid outside the body is assumed to be potential (except for the singularity corresponding to a point vortex), and the flow around the body is noncirculatory. Special attention is given to the general position case in which the point vortex does not lie on the continuations of the semiaxes of the ellipse. The problem under consideration is described by a system of six first-order differential equations. After reduction by the motion group of the plane E(2) it reduces to a system of three differential equations. An analysis of this reduced system is made. It is shown that this system admits one to five fixed points which correspond to motions of the ellipse in various circles. By numerically investigating the phase flow of the reduced system near fixed points, it is shown that, in the general case, the system admits no invariant measure with a smooth positive definite density. Parameter values are found for which one of the fixed points of the reduced system is an unstable node-focus. It is shown that, as the variation of the parameters is continued, an unstable limit cycle can arise from an unstable fixed point via an Andronov – Hopf bifurcation. An analysis is made of bifurcations of this limit cycle for the case where the position of the point vortex relative to the ellipse changes. By constructing a parametric bifurcation diagram, it is shown that, as the system’s parameters are varied, the limit cycle undergoes a cascade of period-doubling bifurcations, giving rise to a chaotic repeller (a reversed-time attractor). To carry out a numerical analysis of the problem, the method of constructing a twodimensional Poincaré map is used. The search for and analysis of simple and strange repellers were performed backward in time.

We study the motion and destruction of Chelyabinsk meteoroid using simple physical and mathematical models. We evaluate the parameters of the motion, taking into account the ablation and mechanical destruction of the meteoroid, and compare our results to the observation data.

The work is devoted to the structural analysis of complex technical systems. Mechanical structures are considered, the properties of which affect the behavior of products during assembly, repair and operation. The main source of data on parts and mechanical connections between them is a hypergraph. This model formalizes the multidimensional basing relation. The hypergraph correctly describes the connectivity and mutual coordination of parts, which is achieved during the assembly of the product. When developing complex products in CAD systems, an engineer often makes serious design mistakes: overbasing of parts and non-sequential assembly operations. Effective ways of identifying these structural defects have been proposed. It is shown that the property of independent assembly can be represented as a closure operator whose domain is the boolean of the set of product parts. The images of this operator are connected and coordinated subsets of parts that can be assembled independently. A lattice model is described, which is the state space of the product during assembly, disassembly and decomposition into assembly units. The lattice model serves as a source of various structural information about the project. Numerical estimates of the cardinality of the set of admissible alternatives in the problems of choosing an assembly sequence and decomposition into assembly units are proposed. For many technical operations (for example, control, testing, etc.), it is necessary to mount all the operand parts in one assembly unit. A simple formalization of the technical conditions requiring the inclusion (exclusion) of parts in the assembly unit (from the assembly unit) has been developed. A theorem that gives an mathematical description of product decomposition into assembly units in exact lattice terms is given. A method for numerical evaluation of the robustness of the mechanical structure of a complex technical system is proposed.

A new method is described for finding parameters of univariate regression model: the greatest cosine method. Implementation of the method involves division of regression model parameters into two groups. The first group of parameters responsible for the angle between the experimental data vector and the regression model vector are defined by the maximum of the cosine of the angle between these vectors. The second group includes the scale factor. It is determined by means of “straightening” the relationship between the experimental data vector and the regression model vector. The interrelation of the greatest cosine method with the method of least squares is examined. Efficiency of the method is illustrated by examples.

The study presented in the paper is devoted to the problem of finite graph exploration using a collective of agents. Finite non-oriented graphs without loops and multiple edges are considered in this paper. The collective of agents consists of two agents-researchers, who have a finite memory independent of the number of nodes of the graph studied by them and use two colors each (three colors are used in the aggregate) and one agentexperimental, who has a finite, unlimitedly growing internal memory. Agents-researches can simultaneously traverse the graph, read and change labels of graph elements, and also transmit the necessary information to a third agent — the agent-experimenter. An agent-experimenter is a non-moving agent in whose memory the result of the functioning of agents-researchers at each step is recorded and, also, a representation of the investigated graph (initially unknown to agents) is gradually built up with a list of edges and a list of nodes.

The work includes detail describes of the operating modes of agents-researchers with an indication of the priority of their activation. The commands exchanged between agents-researchers and an agent-experimenter during the execution of procedures are considered. Problematic situations arising in the work of agentsresearchers are also studied in detail, for example, staining a white vertex, when two agents simultaneously fall into the same node, or marking and examining the isthmus (edges connecting subgraphs examined by different agents-researchers), etc. The full algorithm of the agent-experimenter is presented with a detailed description of the processing of messages received from agents-researchers, on the basis of which a representation of the studied graph is built. In addition, a complete analysis of the time, space, and communication complexities of the constructed algorithm was performed.

The presented graph exploration algorithm has a quadratic (with respect to the number of nodes of the studied graph) time complexity, quadratic space complexity, and quadratic communication complexity. The graph exploration algorithm is based on the depth-first traversal method.

While working on activity recognition using wearable sensors for healthcare applications, the main issue arises in the classification of activities. When we attempt to classify activities like walking, sitting, or running from accelerometer and gyroscope data, the signals often overlap and noise complicates the classification process. The existing methods do not have solid mathematical foundations to handle this issue. We started with the standard magnitude approach where one can compute $m =  \sqrt{a^2_1 + a^2_2 + a^2_3}$ from the accelerometer readings, but this approach failed because different activities ended up in overlapping regions. We therefore developed a different approach. Instead of collapsing the 6-dimensional sensor data into simple magnitudes, we keep all six dimensions and treat each activity as a rectangular box in this 6D space. We define these boxes using simple interval constraints. For example, walking occurs when the $x$-axis accelerometer reading is between $2$ and $4$, the $y$-axis reading is between $9$ and $10$, and so on. The key breakthrough is what we call a separability index $s = \frac{d_{\min}^{}}{\sigma}$ that determines how accurately the classification will work. Here dmin represents how far apart the activity boxes are, and $\sigma$ represents the amount of noise present. From this simple idea, we derive a mathematical formula $P(\text{error}) \leqslant (n-1)\exp\left(-\frac{s^2}8\right)$  that predicts the error rate even before initiating the experiment. We tested this on the standard UCI-HAR and WISDM datasets and achieved $86.1 %$ accuracy. The theoretical predictions matched the actual results within $3 %$. This approach outperforms the traditional magnitude methods by $30.6 %$ and explains why certain activities overlap with each other.

This study develops a previously proposed Method of Computer Analogy (MCA) based on formalization of digital computer operations. The paper discusses the position of the proposed approach among other well-known methods. It is emphasized that the primary objective is to derive analytical solutions, although in some cases they have to resort to semianalytical approximations. The paper focuses on constructing solutions for systems which, for certain parameter values, demonstrate the deterministic chaos behavior, namely Lorenz, Marioka – Shimitsu and R¨ossler systems. The paper also considers obtaining solution for Van der Pol equation (reduced to a nonlinear system). The aim of the study is to construct semi-analytical solutions represented as a segment of a power series in a step size of approximating difference scheme. To prevent overflow, authors formalize rank transfer operation. The authors apply a convergent difference scheme, referred to as the “guiding” scheme, to advance to the next step of the independent variable. The resulting approximation by a sum with only a few terms provides an approximation to the solution with any accuracy in accordance with the accuracy of the governing difference scheme. The senior digits in the resulting approximation exhibit probabilistic properties that can be modeled by known distributions, thereby enabling the derivation of analytical and semi-analytical approximations. The paper presents linear approximations that are the base for a complete approximations of solutions and provide important qualitative as well as some quantitative properties of solutions of considered systems. This work describes approximations of various orders, including those that do not guarantee convergence to the exact solution, but simplify the analysis of certain properties of nonlinear equations and systems. In particular, for the Van der Pol equation, authors demonstrate that its corresponding system has a cyclic solution and provide an estimate of its scale. A modification of the MCA that has features of the Monte Carlo method makes it possible to remove recurrent sequences and construct complete solutions in simple situations. The authors mention a promising approach for representing the solution using branched continued fractions.

The general formalization of visualization models in cellular automata (CA) scope is presented, their classification is examined. It also describes possible approaches to the sound scales generation. We consider special cases of visualization manners for CA of various dimensions. By a simple 3D CA example the features of nanoscale systems imaging are indicated.

The paper reviews the existing approaches to calculating the destruction of solids. The main attention is paid to algorithms using a unified approach to the calculation of deformation both for nondestructive and for the destroyed states of the material. The thermodynamic derivation of the unified rheological relationships taking into account the elastic, viscous and plastic properties of materials and describing the loss of the deformation resistance ability with the accumulation of microdamages is presented. It is shown that the mathematical model under consideration provides a continuous dependence of the solution on input parameters (parameters of the material medium, initial and boundary conditions, discretization parameters) with softening of the material.

Explicit and implicit non-matrix algorithms for calculating the evolution of deformation and fracture development are presented. Non-explicit schemes are implemented using iterations of the conjugate gradient method, with the calculation of each iteration exactly coinciding with the calculation of the time step for two-layer explicit schemes. So, the solution algorithms are very simple.

The results of solving typical problems of destruction of solid deformable bodies for slow (quasistatic) and fast (dynamic) deformation processes are presented. Based on the experience of calculations, recommendations are given for modeling the processes of destruction and ensuring the reliability of numerical solutions.