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In this paper we propose high-order (tensor) methods for two types of saddle point problems. Firstly, we consider the classic min-max saddle point problem. Secondly, we consider the search for a stationary point of the saddle point problem objective by its gradient norm minimization. Obviously, the stationary point does not always coincide with the optimal point. However, if we have a linear optimization problem with linear constraints, the algorithm for gradient norm minimization becomes useful. In this case we can reconstruct the solution of the optimization problem of a primal function from the solution of gradient norm minimization of dual function. In this paper we consider both types of problems with no constraints. Additionally, we assume that the objective function is $\mu$-strongly convex by the first argument, $\mu$-strongly concave by the second argument, and that the $p$-th derivative of the objective is Lipschitz-continous.

For min-max problems we propose two algorithms. Since we consider strongly convex a strongly concave problem, the first algorithm uses the existing tensor method for regular convex concave saddle point problems and accelerates it with the restarts technique. The complexity of such an algorithm is linear. If we additionally assume that our objective is first and second order Lipschitz, we can improve its performance even more. To do this, we can switch to another existing algorithm in its area of quadratic convergence. Thus, we get the second algorithm, which has a global linear convergence rate and a local quadratic convergence rate.

Finally, in convex optimization there exists a special methodology to solve gradient norm minimization problems by tensor methods. Its main idea is to use existing (near-)optimal algorithms inside a special framework. I want to emphasize that inside this framework we do not necessarily need the assumptions of strong convexity, because we can regularize the convex objective in a special way to make it strongly convex. In our article we transfer this framework on convex-concave objective functions and use it with our aforementioned algorithm with a global linear convergence and a local quadratic convergence rate.

Since the saddle point problem is a particular case of the monotone variation inequality problem, the proposed methods will also work in solving strongly monotone variational inequality problems.

Protection of aquatic biological resources in the coastal area has significant features (a large number of small fishing vessels, the dynamism of the situation, the use of coastal protection), by virtue of which stands in a class of applications. A mathematical model of protection designed for the determination of detection equipment and means of violators of the situation in order to ensure the function of deterrence of illegal activities. Resolves a tactical game-theoretic problem - find the optimal line patrol (parking) means of implementation (guard boats) and optimal removal of seats from the shore fishing violators. Using the methods of the theory of experimental design, linear regression models to assess the contribution of the main factors affecting the results of the simulation.

In order to enhance the sustainability and adequacy of the model is proposed to use the mechanism of rankings means of protection, based on the borders and the rank and Pareto allows to take into account the principles of protection and further means of protection. To account for the variability of the situation offered several scenarios in which it is advisable to perform calculations.

The article presents the numerical modeling and study of the kinetic model of propane pyrolysis. The study of the reaction kinetics is a necessary stage in modeling the dynamics of the gas flow in the reactor.

The kinetic model of propane pyrolysis is a nonlinear system of ordinary differential equations of the first order with parameters, the role of which is played by the reaction rate constants. Math modeling of processes is based on the use of the mass conservation law. To solve an initial (forward) problem, implicit methods for solving stiff ordinary differential equation systems are used. The model contains 60 input kinetic parameters and 17 output parameters corresponding to the reaction substances, of which only 9 are observable. In the process of solving the problem of estimating parameters (inverse problem), there is a question of non-uniqueness of the set of parameters that satisfy the experimental data. Therefore, before solving the inverse problem, the possibility of determining the parameters of the model is analyzed (analysis of identifiability).

To analyze identifiability, we use the orthogonal method, which has proven itself well for analyzing models with a large number of parameters. The algorithm is based on the analysis of the sensitivity matrix by the methods of differential and linear algebra, which shows the degree of dependence of the unknown parameters of the models on the given measurements. The analysis of sensitivity and identifiability showed that the parameters of the model are stably determined from a given set of experimental data. The article presents a list of model parameters from most to least identifiable. Taking into account the analysis of the identifiability of the mathematical model, restrictions were introduced on the search for less identifiable parameters when solving the inverse problem.

The inverse problem of estimating the parameters was solved using a genetic algorithm. The article presents the found optimal values of the kinetic parameters. A comparison of the experimental and calculated dependences of the concentrations of propane, main and by-products of the reaction on temperature for different flow rates of the mixture is presented. The conclusion about the adequacy of the constructed mathematical model is made on the basis of the correspondence of the results obtained to physicochemical laws and experimental data.

The paper gives a detailed description of the developed methods for simulating the turbulent flow around a helicopter rotor and calculating its aerodynamic characteristics. The system of Reynolds-averaged Navier – Stokes equations for a viscous compressible gas closed by the Spalart –Allmaras turbulence model is used as the basic mathematical model. The model is formulated in a non-inertial rotating coordinate system associated with a rotor. To set the boundary conditions on the surface of the rotor, wall functions are used.

The numerical solution of the resulting system of differential equations is carried out on mixed-element unstructured grids including prismatic layers near the surface of a streamlined body.The numerical method is based on the original vertex-centered finite-volume EBR schemes. A feature of these schemes is their higher accuracy which is achieved through the use of edge-based reconstruction of variables on extended quasi-onedimensional stencils, and a moderate computational cost which allows for serial computations. The methods of Roe and Lax – Friedrichs are used as approximate Riemann solvers. The Roe method is corrected in the case of low Mach flows. When dealing with discontinuities or solutions with large gradients, a quasi-one-dimensional WENO scheme or local switching to a quasi-one-dimensional TVD-type reconstruction is used. The time integration is carried out according to the implicit three-layer second-order scheme with Newton linearization of the system of difference equations. To solve the system of linear equations, the stabilized conjugate gradient method is used.

The numerical methods are implemented as a part of the in-house code NOISEtte according to the two-level MPI–OpenMP parallel model, which allows high-performance computations on meshes consisting of hundreds of millions of nodes, while involving hundreds of thousands of CPU cores of modern supercomputers.

Based on the results of numerical simulation, the aerodynamic characteristics of the helicopter rotor are calculated, namely, trust, torque and their dimensionless coefficients.

Validation of the developed technique is carried out by simulating the turbulent flow around the Caradonna – Tung two-blade rotor and the KNRTU-KAI four-blade model rotor in hover mode mode, tail rotor in duct, and rigid main rotor in oblique flow. The numerical results are compared with the available experimental data.

This paper is devoted to some variants of improving the convergence rate guarantees of the gradient-type algorithms for relatively smooth and relatively Lipschitz-continuous problems in the case of additional information about some analogues of the strong convexity of the objective function. We consider two classes of problems, namely, convex problems with a relative functional growth condition, and problems (generally, non-convex) with an analogue of the Polyak – Lojasiewicz gradient dominance condition with respect to Bregman divergence. For the first type of problems, we propose two restart schemes for the gradient type methods and justify theoretical estimates of the convergence of two algorithms with adaptively chosen parameters corresponding to the relative smoothness or Lipschitz property of the objective function. The first of these algorithms is simpler in terms of the stopping criterion from the iteration, but for this algorithm, the near-optimal computational guarantees are justified only on the class of relatively Lipschitz-continuous problems. The restart procedure of another algorithm, in its turn, allowed us to obtain more universal theoretical results. We proved a near-optimal estimate of the complexity on the class of convex relatively Lipschitz continuous problems with a functional growth condition. We also obtained linear convergence rate guarantees on the class of relatively smooth problems with a functional growth condition. For a class of problems with an analogue of the gradient dominance condition with respect to the Bregman divergence, estimates of the quality of the output solution were obtained using adaptively selected parameters. We also present the results of some computational experiments illustrating the performance of the methods for the second approach at the conclusion of the paper. As examples, we considered a linear inverse Poisson problem (minimizing the Kullback – Leibler divergence), its regularized version which allows guaranteeing a relative strong convexity of the objective function, as well as an example of a relatively smooth and relatively strongly convex problem. In particular, calculations show that a relatively strongly convex function may not satisfy the relative variant of the gradient dominance condition.

The work is devoted to the construction and analysis of difference schemes for a system of hemodynamic equations obtained by averaging the hydrodynamic equations of a viscous incompressible fluid over the vessel cross-section. Models of blood as an ideal and as a viscous Newtonian fluid are considered. Difference schemes that approximate equations with second order on the spatial variable are proposed. The computational algorithms of the constructed schemes are based on the method of splitting on physical processes. According to this approach, at one time step, the model equations are considered separately and sequentially. The practical implementation of the proposed schemes at each time step leads to a sequential solution of two linear systems with tridiagonal matrices. It is demonstrated that the schemes are $\rho$-stable under minor restrictions on the time step in the case of sufficiently smooth solutions.

For the problem with a known analytical solution, it is demonstrated that the numerical solution has a second order convergence in a wide range of spatial grid step. The proposed schemes are compared with well-known explicit schemes, such as the Lax – Wendroff, Lax – Friedrichs and McCormack schemes in computational experiments on modeling blood flow in model vascular systems. It is demonstrated that the results obtained using the proposed schemes are close to the results obtained using other computational schemes, including schemes constructed by other approaches to spatial discretization. It is demonstrated that in the case of different spatial grids, the time of computation for the proposed schemes is significantly less than in the case of explicit schemes, despite the need to solve systems of linear equations at each step. The disadvantages of the schemes are the limitation on the time step in the case of discontinuous or strongly changing solutions and the need to use extrapolation of values at the boundary points of the vessels. In this regard, problems on the adaptation of splitting schemes for problems with discontinuous solutions and in cases of special types of conditions at the vessels ends are perspective for further research.

The article considers a bilinear model of the influence of external disturbances on the stability of the structure of social systems. Approaches to the third-party stabilization of the initial system consisting of two groups are investigated — by reducing the initial system to a linear system with uncertain parameters and using the results of the theory of linear dynamic games with a quadratic criterion. The influence of the coefficients of the proposed model of the social system and the control parameters on the quality of the system stabilization is analyzed with the help of computer experiments. It is shown that the use of a minimax strategy by a third party in the form of feedback control leads to a relatively close convergence of the population of the second group (excited by external influences) to an acceptable level, even with unfavorable periodic dynamic perturbations.

The influence of one of the key coefficients in the criterion $(\varepsilon)$ used to compensate for the effects of external disturbances (the latter are present in the linear model in the form of uncertainty) on the quality of system stabilization is investigated. Using Z-transform, it is shown that a decrease in the coefficient $\varepsilon$ should lead to an increase in the values of the sum of the squares of the control. The computer calculations carried out in the article also show that the improvement of the convergence of the system structure to the equilibrium level with a decrease in this coefficient is achieved due to sharp changes in control in the initial period, which may induce the transition of some members of the quiet group to the second, excited group.

The article also examines the influence of the values of the model coefficients that characterize the level of social tension on the quality of management. Calculations show that an increase in the level of social tension (all other things being equal) leads to the need for a significant increase in the third party's stabilizing efforts, as well as the value of control at the transition period.

The results of the statistical modeling carried out in the article show that the calculated feedback controls successfully compensate for random disturbances on the social system (both in the form of «white» noise, and of autocorrelated disturbances).

The paper studies the problem of searching for fragments with missing bibliographic links in a scientific article using automatic binary classification. To train the model, we propose a new contrast resampling technique, the innovation of which is the consideration of the context of the link, taking into account the boundaries of the fragment, which mostly affects the probability of presence of a bibliographic links in it. The training set was formed of automatically labeled samples that are fragments of three sentences with class labels «without link» and «with link» that satisfy the requirement of contrast: samples of different classes are distanced in the source text. The feature space was built automatically based on the term occurrence statistics and was expanded by constructing additional features — entities (names, numbers, quotes and abbreviations) recognized in the text.

A series of experiments was carried out on the archives of the scientific journals «Law enforcement review» (273 articles) and «Journal Infectology» (684 articles). The classification was carried out by the models Nearest Neighbors, RBF SVM, Random Forest, Multilayer Perceptron, with the selection of optimal hyperparameters for each classifier.

Experiments have confirmed the hypothesis put forward. The highest accuracy was reached by the neural network classifier (95%), which is however not as fast as the linear one that showed also high accuracy with contrast resampling (91–94%). These values are superior to those reported for NER and Sentiment Analysis on comparable data. The high computational efficiency of the proposed method makes it possible to integrate it into applied systems and to process documents online.

Modern power transportation systems are the complex engineering systems. Such systems include both point facilities (power producers, consumers, transformer substations, etc.) and the distributed elements (f.e. power lines). Such structures are presented in the form of the graphs with different types of nodes under creating the mathematical models. It is necessary to solve the system of partial differential equations of the hyperbolic type to study the dynamic effects in such systems.

An approach similar to one already applied in modeling similar problems earlier used in the work. New variant of the splitting method was used proposed by the authors. Unlike most known works, the splitting is not carried out according to physical processes (energy transport without dissipation, separately dissipative processes). We used splitting to the transport equations with the drain and the exchange between Reimann’s invariants. This splitting makes possible to construct the hybrid schemes for Riemann invariants with a high order of approximation and minimal dissipation error. An example of constructing such a hybrid differential scheme is described for a single-phase power line. The difference scheme proposed is based on the analysis of the properties of the schemes in the space of insufficient coefficients.

Examples of the model problem numerical solutions using the proposed splitting and the difference scheme are given. The results of the numerical calculations shows that the difference scheme allows to reproduce the arising regions of large gradients. It is shown that the difference schemes also allow detecting resonances in such the systems.

Distributed saddle point problems (SPPs) have numerous applications in optimization, matrix games and machine learning. For example, the training of generated adversarial networks is represented as a min-max optimization problem, and training regularized linear models can be reformulated as an SPP as well. This paper studies distributed nonsmooth SPPs with Lipschitz-continuous objective functions. The objective function is represented as a sum of several components that are distributed between groups of computational nodes. The nodes, or agents, exchange information through some communication network that may be centralized or decentralized. A centralized network has a universal information aggregator (a server, or master node) that directly communicates to each of the agents and therefore can coordinate the optimization process. In a decentralized network, all the nodes are equal, the server node is not present, and each agent only communicates to its immediate neighbors.

We assume that each of the nodes locally holds its objective and can compute its value at given points, i. e. has access to zero-order oracle. Zero-order information is used when the gradient of the function is costly, not possible to compute or when the function is not differentiable. For example, in reinforcement learning one needs to generate a trajectory to evaluate the current policy. This policy evaluation process can be interpreted as the computation of the function value. We propose an approach that uses a smoothing technique, i. e., applies a first-order method to the smoothed version of the initial function. It can be shown that the stochastic gradient of the smoothed function can be viewed as a random two-point gradient approximation of the initial function. Smoothing approaches have been studied for distributed zero-order minimization, and our paper generalizes the smoothing technique on SPPs.