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The simplest and most desirable method of traffic signal control is precalculated regulation, when the parameters of the traffic light object operation are calculated in advance and activated in accordance to a schedule. This work proposes a method of forming a signal plan that allows one to calculate the control programs and set the period of their activity. Preparation of initial data for the calculation includes the formation of a time series of daily traffic intensity with an interval of 15 minutes. When carrying out field studies, it is possible that part of the traffic intensity measurements is missing. To fill up the missing traffic intensity measurements, the spline interpolation method is used. The next step of the method is to calculate the daily set of signal plans. The work presents the interdependencies, which allow one to calculate the optimal durations of the control cycle and the permitting phase movement and to set the period of their activity. The present movement control systems have a limit on the number of control programs. To reduce the signal plans' number and to determine their activity period, the clusterization using the $k$-means method in the transport phase space is introduced In the new daily signal plan, the duration of the phases is determined by the coordinates of the received cluster centers, and the activity periods are set by the elements included in the cluster. Testing on a numerical illustration showed that, when the number of clusters is 10, the deviation of the optimal phase duration from the cluster centers does not exceed 2 seconds. To evaluate the effectiveness of the developed methodology, a real intersection with traffic light regulation was considered as an example. Based on field studies of traffic patterns and traffic demand, a microscopic model for the SUMO (Simulation of Urban Mobility) program was developed. The efficiency assessment is based on the transport losses estimated by the time spent on movement. Simulation modeling of the multiprogram control of traffic lights showed a 20% reduction in the delay time at the traffic light object in comparison with the single-program control. The proposed method allows automation of the process of calculating daily signal plans and setting the time of their activity.

In this study we discuss methods to solve optimal control problems based on neural network techniques. We study hierarchical dynamical two-level system for surface water quality control. The system consists of a supervisor (government) and a few agents (enterprises). We consider this problem from the point of agents. In this case we solve optimal control problem with constraints. To solve this problem, we use Pontryagin’s maximum principle, with which we obtain optimality conditions. To solve emerging ODEs, we use feedforward neural network. We provide a review of existing techniques to study such problems and a review of neural network’s training methods. To estimate the error of numerical solution, we propose to use defect analysis method, adapted for neural networks. This allows one to get quantitative error estimations of numerical solution. We provide examples of our method’s usage for solving synthetic problem and a surface water quality control model. We compare the results of this examples with known solution (when provided) and the results of shooting method. In all cases the errors, estimated by our method are of the same order as the errors compared with known solution. Moreover, we study surface water quality control problem when no solutions is provided by other methods. This happens because of relatively large time interval and/or the case of several agents. In the latter case we seek Nash equilibrium between agents. Thus, in this study we show the ability of neural networks to solve various problems including optimal control problems and differential games and we show the ability of quantitative estimation of an error. From the numerical results we conclude that the presence of the supervisor is necessary for achieving the sustainable development.

The paper considers the possibility of comparing and classifying dynamical systems based on topological data analysis. Determining the measures of interaction between the channels of dynamic systems based on the HIIA (Hankel Interaction Index Array) and PM (Participation Matrix) methods allows you to build HIIA and PM graphs and their adjacency matrices. For any linear dynamic system, an approximating directed graph can be constructed, the vertices of which correspond to the components of the state vector of the dynamic system, and the arcs correspond to the measures of mutual influence of the components of the state vector. Building a measure of distance (proximity) between graphs of different dynamic systems is important, for example, for identifying normal operation or failures of a dynamic system or a control system. To compare and classify dynamic systems, weighted directed graphs corresponding to dynamic systems are preliminarily formed with edge weights corresponding to the measures of interaction between the channels of the dynamic system. Based on the HIIA and PM methods, matrices of measures of interaction between the channels of dynamic systems are determined. The paper gives examples of the formation of weighted directed graphs for various dynamic systems and estimation of the distance between these systems based on topological data analysis. An example of the formation of a weighted directed graph for a dynamic system corresponding to the control system for the components of the angular velocity vector of an aircraft, which is considered as a rigid body with principal moments of inertia, is given. The method of topological data analysis used in this work to estimate the distance between the structures of dynamic systems is based on the formation of persistent barcodes and persistent landscape functions. Methods for comparing dynamic systems based on topological data analysis can be used in the classification of dynamic systems and control systems. The use of traditional algebraic topology for the analysis of objects does not allow obtaining a sufficient amount of information due to a decrease in the data dimension (due to the loss of geometric information). Methods of topological data analysis provide a balance between reducing the data dimension and characterizing the internal structure of an object. In this paper, topological data analysis methods are used, based on the use of Vietoris-Rips and Dowker filtering to assign a geometric dimension to each topological feature. Persistent landscape functions are used to map the persistent diagrams of the method of topological data analysis into the Hilbert space and then quantify the comparison of dynamic systems. Based on the construction of persistent landscape functions, we propose a comparison of graphs of dynamical systems and finding distances between dynamical systems. For this purpose, weighted directed graphs corresponding to dynamical systems are preliminarily formed. Examples of finding the distance between objects (dynamic systems) are given.

The paper presents the results of numerical simulation of different-temperature water flows turbulent mixing in a T-junctions in the FlowVision software package. The article describes in detail an experimental stand specially designed to obtain boundary conditions that are simple for most computational fluid dynamics software systems. Values of timeaveraged temperatures and velocities in the control sensors and planes were obtained according to the test results. The article presents the system of partial differential equations used in the calculation describing the process of heat and mass transfer in a liquid using the Smagorinsky turbulence model. Boundary conditions are specified that allow setting the random velocity pulsations at the entrance to the computational domain. Distributions of time-averaged water velocity and temperature in control sections and sensors are obtained. The simulation is performed on various computational grids, for which the axes of the global coordinate system coincide with the directions of hot and cold water flows. The possibility for FlowVision PC to construct a computational grid in the simulation process based on changes in flow parameters is shown. The influence of such an algorithm for constructing a computational grid on the results of calculations is estimated. The results of calculations on a diagonal grid using a beveled scheme are given (the direction of the coordinate lines does not coincide with the direction of the tee pipes). The high efficiency of the beveled scheme is shown when modeling flows whose general direction does not coincide with the faces of the calculated cells. A comparison of simulation results on various computational grids is carried out. The numerical results obtained in the FlowVision PC are compared with experimental data and calculations performed using other computing programs. The results of modeling turbulent mixing of water flow of different temperatures in the FlowVision PC are closer to experimental data in comparison with calculations in CFX ANSYS. It is shown that the application of the LES turbulence model on relatively small computational grids in the FlowVision PC allows obtaining results with an error within 5%.

Many nonlinear control systems by nonsingular transformation variable {condition-control} happen to canonical Brunovsky form. The different questions dare in canonical form to theories of control, then inverse change variable is realized return to source variable. In work on base this ideology are studied transformations to symmetries space {time-condition-control}.

A model of forest insect population dynamics used to simulate of “forest-insect” interactions and for estimation of possible damages of forest stand by pests. This model represented a population as control system where the input variables characterized the influence of modifier (climatic) factors and the feedback loop describes the effect of regulatory factors (parasites, predators and population interactions). The technique of stress testing on the basis of population dynamics model proposed for assessment of the risks of forest stand damage and destruction after insect impact. The dangerous forest pest pine looper Bupalus piniarius L. considered as the object of analysis. Computer experiments were conducted to assess of outbreak risks with possible climate change in the territory of Central Siberia. Model experiments have shown that risk of insect impact on the forest is not increased significantly in condition of sufficiently moderate warming (not more than 4 °C in summer period). However, a stronger warming in the territory of Central Siberia, combined with a dry summer condition could cause a significant increase in the risk of pine looper outbreaks.

Efficiency of production directly depends on quality of the management of technology which, in turn, relies on the accuracy and efficiency of the processing of control and measuring information. Development of the mathematical methods of research of the system communications and regularities of functioning and creation of the mathematical models taking into account structural features of object of researches, and also writing of the software products for realization of these methods are an actual task. Practice has shown that the list of parameters that take place in the study of complex object of modern production, ranging from a few dozen to several hundred names, and the degree of influence of each factor in the initial time is not clear. Before working for the direct determination of the model in these circumstances, it is impossible — the amount of the required information may be too great, and most of the work on the collection of this information will be done in vain due to the fact that the degree of influence on the optimization of most factors of the original list would be negligible. Therefore, a necessary step in determining a model of a complex object is to work to reduce the dimension of the factor space. Most industrial plants are hierarchical group processes and mass volume production, characterized by hundreds of factors. (For an example of realization of the mathematical methods and the approbation of the constructed models data of the Moldavian steel works were taken in a basis.) To investigate the systemic linkages and patterns of functioning of such complex objects are usually chosen several informative parameters, and carried out their sampling. In this article the sequence of coercion of the initial indices of the technological process of the smelting of steel to the look suitable for creation of a mathematical model for the purpose of prediction is described. The implementations of new types became also creation of a basis for development of the system of automated management of quality of the production. In the course of weak correlation the following stages are selected: collection and the analysis of the basic data, creation of the table the correlated of the parameters, abbreviation of factor space by means of the correlative pleiads and a method of weight factors. The received results allow to optimize process of creation of the model of multiple-factor process.

Optical systems with two-dimensional feedback demonstrate wide possibilities for studying the nucleation and development processes of dissipative structures. Feedback allows to influence the dynamics of the optical system by controlling the transformation of spatial variables performed by prisms, lenses, dynamic holograms and other devices. A nonlinear interferometer with a mirror image of a field in two-dimensional feedback is one of the simplest optical systems in which is realized the nonlocal nature of light fields.

A mathematical model of optical systems with two-dimensional feedback is a nonlinear parabolic equation with rotation transformation of a spatial variable and periodicity conditions on a circle. Such problems are investigated: bifurcation of the traveling wave type stationary structures, how the form of the solution changes as the diffusion coefficient decreases, dynamics of the solution’s stability when the bifurcation parameter leaves the critical value. For the first time as a parameter bifurcation was taken of diffusion coefficient.

The method of central manifolds and the Galerkin’s method are used in this paper. The method of central manifolds and the Galerkin’s method are used in this paper. The method of central manifolds allows to prove a theorem on the existence and form of the traveling wave type solution neighborhood of the bifurcation value. The first traveling wave born as a result of the Andronov –Hopf bifurcation in the transition of the bifurcation parameter through the сritical value. According to the central manifold theorem, the first traveling wave is born orbitally stable.

Since the above theorem gives the opportunity to explore solutions are born only in the vicinity of the critical values of the bifurcation parameter, the decision to study the dynamics of traveling waves of change during the withdrawal of the bifurcation parameter in the supercritical region, the formalism of the Galerkin method was used. In accordance with the method of the central manifold is made Galerkin’s approximation of the problem solution. As the bifurcation parameter decreases and its transition through the critical value, the zero solution of the problem loses stability in an oscillatory manner. As a result, a periodic solution of the traveling wave type branches off from the zero solution. This wave is born orbitally stable. With further reduction of the parameter and its passage through the next critical value from the zero solution, the second solution of the traveling wave type is produced as a result of the Andronov –Hopf bifurcation. This wave is born unstable with an instability index of two.

Numerical calculations have shown that the application of the Galerkin’s method leads to correct results. The results obtained are in good agreement with the results obtained by other authors and can be used to establish experiments on the study of phenomena in optical systems with feedback.

The purpose of the paper is a research of a 2nd order finite difference scheme based on the Z-scheme. This research is the numerical solution of several two-dimensional differential equations simulated the incompressible medium convection.

One of real tasks for similar equations solution is the numerical simulating of strongly non-stationary midscale processes in the Earth ionosphere. Because convection processes in ionospheric plasma are controlled by magnetic field, the plasma incompressibility condition is supposed across the magnetic field. For the same reason, there can be rather high velocities of heat and mass convection along the magnetic field.

Ionospheric simulation relevant task is the research of plasma instability of various scales which started in polar and equatorial regions first of all. At the same time the mid-scale irregularities having characteristic sizes 1–50 km create conditions for development of the small-scale instabilities. The last lead to the F-spread phenomenon which significantly influences the accuracy of positioning satellite systems work and also other space and ground-based radio-electronic systems.

The difference schemes used for simultaneous simulating of such multi-scale processes must to have high resolution. Besides, these difference schemes must to be high resolution on the one hand and monotonic on the other hand. The fact that instabilities strengthen errors of difference schemes, especially they strengthen errors of dispersion type is the reason of such contradictory requirements. The similar swing of errors usually results to nonphysical results at the numerical solution.

At the numerical solution of three-dimensional mathematical models of ionospheric plasma are used the following scheme of splitting on physical processes: the first step of splitting carries out convection along, the second step of splitting carries out convection across. The 2nd order finite difference scheme investigated in the paper solves approximately convection across equations. This scheme is constructed by a monotonized nonlinear procedure on base of the Z-scheme which is one of 2nd order schemes. At this monotonized procedure a nonlinear correction with so-called “oblique differences” is used. “Oblique differences” contain the grid nodes relating to different layers of time.

The researches were conducted for two cases. In the simulating field components of the convection vector had: 1) the constant sign; 2) the variable sign. Dissipative and dispersive characteristics of the scheme for different types of the limiting functions are in number received.

The results of the numerical experiments allow to draw the following conclusions.

1. For the discontinuous initial profile the best properties were shown by the SuperBee limiter.

2. For the continuous initial profile with the big spatial steps the SuperBee limiter is better, and at the small steps the Koren limiter is better.

3. For the smooth initial profile the best results were shown by the Koren limiter.

4. The smooth F limiter showed the results similar to Koren limiter.

5. Limiters of different type leave dispersive errors, at the same time dependences of dispersive errors on the scheme parameters have big variability and depend on the scheme parameters difficulty.

6. The monotony of the considered differential scheme is in number confirmed in all calculations. The property of variation non-increase for all specified functions limiters is in number confirmed for the onedimensional equation.

7. The constructed differential scheme at the steps on time which are not exceeding the Courant's step is monotonous and shows good exactness characteristics for different types solutions. At excess of the Courant's step the scheme remains steady, but becomes unsuitable for instability problems as monotony conditions not satisfied in this case.

Correct modeling of complex dynamics of urban transportation flows requires the collection of large volumes of empirical data to specify types of the modes and their identification. At the same time, setting a large number of observation posts is expensive and technically not always feasible. All this results in insufficient factographic support for the traffic control systems as well as for urban planners with the obvious consequences for the quality of their decisions. As one of the means to provide large-scale data collection at least for the qualitative situation analysis, the wide-area video cameras are used in different situation centers. There they are analyzed by human operators who are responsible for observation and control. Some video cameras provided their videos for common access, which makes them a valuable resource for transportation studies. However, there are significant problems with getting qualitative data from such cameras, which relate to the theory and practice of image processing. This study is devoted to the practical application of certain mainstream neuro-networking technologies for the estimation of essential characteristics of actual transportation flows. The problems arising in processing these data are analyzed, and their solutions are suggested. The convolution neural networks are used for tracking, and the methods for obtaining basic parameters of transportation flows from these observations are studied. The simplified neural networks are used for the preparation of training sets for the deep learning neural network YOLOv4 which is later used for the estimation of speed and density of automobile flows.