The paper proposes an approach to managing the functioning of an engineering network based on the integration of structural models of a resource-supplying organization managing processes and a graph model of the network itself. The peculiarity of the approach is that the damage in case of accidents of engineering networks arising from errors in the management processes of the resource-supplying organization is assessed. The problem of finding errors in processes is solved, both static, arising during the design of processes, and in the mode of their functioning, i.e. in dynamics.

The article discusses the application of random search method for finding the extremal value of a function that depends on multiple parameters. The advantages and disadvantages of the method are described, as well as the possibility of improving it using machine learning methods. Using the example of quantitative analysis of multicomponent mixtures, it is shown how random search method can be combined with machine learning methods to solve the problem of parametric identification.

The article deals with the urgent problem of the priority choice of rural settlements, where it is necessary to improve the conditions for the provision of medical care. For a conceptual understanding of the problem of choosing the optimal solution, a brief thesaurus has been formed and an ontology of the subject area has been developed. As the main selection algorithm, it is proposed to use an algorithm for solving a multicriteria problem based on the theory of antagonistic games, taking into account incomplete information about the preferences of the decision maker. The authors of the article proposed a multi-parameter decision-making model, which includes three main groups of criteria: the availability of medical care, the parameters of the building and the parameters of the medical staff. To prepare data with settlement parameters, nearest neighbor clustering and centroid ratio methods are used. The results of processing the data matrix of the Oeksky bush of the Irkutsk region were tabular data and a graphical display of clusters and their centers on the axis of geographical coordinates. The modified algorithm for processing two matrices made it possible to calculate the optimal distances within the clusters. The solution of the problem of multi-criteria choice on the example of one cluster of the subject of the Russian Federation according to the chosen preferences of the decision maker made it possible to reasonably formulate arguments for making a decision. The developed data model and algorithms for determining the selection parameters can be used as the basis for the formation of the terms of reference for the development of a full-featured expert-oriented system that can raise the quality of decision making to a higher level.

The article discusses the software structure of a web application for displaying data from a temperature profiler. Modules for data formation and retrieval are described, which are used to create graphical materials, and examples of constructed graphs are illustrated. Also considered are the tools and libraries that were used to create this web application.

The article is devoted to the description of the thesaurus on information technologies developed within the framework of the target program for the development of information resources of the Department "Electronic Library of the Siberian Branch of the Russian Academy of Sciences". The thesaurus is actively used in the educational process of NSU students, as well as for automatic communication of documents in the electronic library created and operated at the FRC ICT. To implement the thesaurus, the Zthes data scheme was chosen, the main advantage of which is its compliance with the Z39.50 network protocol model, which allows not only to work with its own local thesaurus, but also to connect, if necessary, thesauri located on the network. New elements have been added to the Zthes data schema by the developers. Currently, the thesaurus is implemented in threelanguages (Russian, Kazakh and English) and contains over 20,000 terms.

The article considers the application of the indicative method for assessing the energy security of the regions of the Republic of Belarus, calculates the integral indicator of the energy security of the regions using the indicative approach.

This work is the first of a series of articles devoted to the application of the developed digital twin technology of a complex technical system for the study of its properties. One of these properties is resilience, which is understood as the property of these energy complexes to adapt to large disturbances and restore their initial state after their impact. Autonomous micro-networks are considered as complex technical systems in the article. The study of the resilience of these local-level energy complexes is usually based on multivariate computational experiments, however, if there is a feedback of a digital twin with a micro-grid or a test bench, field experiments can also be used. The key component of the digital twin of the microgrid should be a complex of various models that accurately describe all aspects of the behavior of this energy complex. This article describes an optimization model of a microgrid based on the concept of an energy hub. The energy hub concentrates production capacities for generating, converting and accumulating energy resources, which are connected to each other and to consumers using energy transport networks. The article presents a software implementation of an optimization model of a microgrid based on the concept of an energy hub. In conclusion, a comparison is made with a fundamentally similar two-level model of the city's energy complex, showing that the modeling of a microgrid based on the concept of an energy hub provides higher computational efficiency. On the other hand, the model of the energy complex of the city more accurately than the microgrid model presented in this article reflects the physical features of some processes, for example, the transport of heat and electricity.

This paper considers the modeling of a test power system with three nodes to analyze the effectiveness of using nonlinear models of thermal power plants in the study of energy security and reliability of power supply. Within the framework of the modeling, experiments were conducted using various types of generating equipment and loads, as well as calculations based on nonlinear models. The results of the simulation showed that the use of nonlinear models makes it possible to more accurately assess the level of energy security and energy supply reliability, which can be useful in planning and designing energy systems.

There is physico-mathematics dependences conclusion of a finite element method for the Timoshenko beam finite element at the article, which is working by the shear bend at static and dynamic load conditions and allows more accurately approximate displacement field in comparison with the classical bending theory. It's shown, the softening of a finite element in this case is resultant of two components compose: “bending” caused by the bending moment action and “shear”, caused by the shear force action, and cross section angle is different from the beam elastic axis tangent angle; also the shear softening is appeared at short beams, where length is commensurable with height of the beam cross section. The mathematical model is built by the base of variational energy principle of the finite element method. For the indicated type of finite element, polynomial shape functions are obtained, which serve to approximate the displacement field, using differential dependencies known from the courses of resistance of materials and the theory of elasticity. There was gotten the gradient matrix, which allows to determine the deformation vector by the values of the node translation pole and the stiffness matrix, which is had the key meaning at the solving of the system of linear algebraic equations of the finite element method, value of the stress vector and internal force factors at the shear bending, which allows to determine it by the nodes translations. For the finite element model was made convergence analysis of the numerical finite element method by relative to the analytical calculation and are shown results deviation when the model of pure bending and Timoshenko beam model were used.

The results of applying the invariance conditions as the basic principle of the synergetic control theory to stochastic objects of bioengineering orientation: immunology, biological treatment systems and the simplest ecosystem model are presented. It is shown on three nonlinear control objects that the assumptions of controllability of the object in the state space and the analytical description of the target invariant of the system are sufficient conditions for the existence of a stochastic controller that minimizes the variance of the output macrovariable when the random control object is output to the target set of states.

The article presents a functional diagram of the control system of the electric drive of a walking excavator. Structural-parametric models of DC electric drives of an excavator with a pulse-phase control system and a pulse-frequency control system have been developed. Simulation of DC electric drives of an excavator with a pulse-phase control system and a pulse-frequency control system in the Matlab/Simulink environment was carried out. A comparison of the results of modeling control systems is given.

The article discusses three linear programming models for optimizing the production of agricultural products in conditions of land heterogeneity. The first model describes a combination of crop and livestock industries. The second parametric programming model allows you to plan the production of agricultural products for a certain perspective. The third model characterizes the situation of optimizing the production of agricultural products under conditions of risks. Examples of the implementation of the developed models are given.

Previously, the author proposed modular linear regression models containing as regressors modules of deviations of the values of explanatory variables from unknown coefficients. An algorithm for their exact estimation using the least absolute deviation and an algorithm for approximate estimation using the least squares method is known. Software products implementing these algorithms have not been developed until today. This article is devoted to the description of the software package developed by the author for evaluating modular linear regressions (PC MODULIR-1). In it, when evaluating modular linear regression using the method of smallest modules according to the specified settings, a mixed-integer 0-1 linear programming problem for the LPSolve package is automatically generated. And in the case of approximate estimation using the least squares method, a complete search of all possible model variants is carried out and the best modular regression with all coefficients significant according to the Student's t-test is selected. The problem of modeling the freight turnover of railway transport in the Zabaykalsky krai was solved with the help of PC MODULAR-1. The coefficient of determination of the modular regression constructed using the least squares method with five explanatory variables was 0.94, which is about 4 times higher than that of traditional linear regression. At the same time, all the coefficients of modular regression turned out to be significant according to the Student's t-test. It is shown how the constructed modular regression can be interpreted.

The paper discusses the proposed experimental-theoretical approach for estimating the parameters of the macrokinetics of hydration of multicomponent cement systems with partial replacement of cement with silica fume and zeolite. Activation energy parameters are necessary to analyze the reactivity of the components used and to model the process of curing concrete from the standpoint of a model of related physical and chemical processes in reacting media. Isothermal calorimetry is used to determine the macrokinetic parameters of hydration. The calculation results showed the effectiveness of this approach for obtaining information about the activity of the investigated complex binders and their modeling.

The approach and an algorithm that implements it are presented for application to the problem of generating a musical composition. The initial data are interpreted as a non-stationary time series, to which the mode decomposition method is applied, followed by the original processing of the internal mode functions to construct the prediction rule.