Abstract-The subject matter of the article is developing information and communication network (ICN) for critical infrastructure systems (CIS). The aim of the work is to provide high-quality information and telecommunication processes by developing the optimal version of distributing CIS functional tasks and ICN processes to the network nodes. The article deals with following problems: developing a model for mapping the information and technical ICN structures, developing a method for variant synthesis of ITS structural models, a formalized representation of the problem of selecting CIS optimal structure. The methods used are: the system method, the set-theoretic and graphic analytic approaches, methods of hierarchic structures synthesis, optimization methods. The following results were obtained: the use of system approach for formalizing the information processing process in CIS was justified; mapping the ICS functional system into the information and technical one was presented as multilevel graph chain; the generalized representation of graph structures hierarchy was developed for the set of data transmitting tasks; this approach enabled formal representing alternative variants that consider the main links, sequencing, the amount and flows of the processed information among the different structure levels; the scheme of variant synthesis method of ICN models according to graph structures mapping was developed; the problem of selecting optimal ICN structures was formally presented; a complex efficiency criterion for solving problems of optimizing variant synthesis of structures; the problem of optimal synthesis of the structure of the given level factored in resource constraints was formulated. Conclusions. The article deals with such novelty aspects as improving the model of problem of selecting the optimal ICN structure by settheoretic formalization factored in the criterion of maximum intensity of computational resource application, which enabled determining structural links among the major elements considering the decomposition of the model up to the basic elements such as "node" and "task" and the development of a new method of optimal ICN structuring which unlike the existing ones involves the variant synthesis of structures hierarchy and formalizing selection problems on the basis of settheoretic models, which enables providing the efficiency of application of information and technical net resources.

The subject matter of the article is the processes of analysis and risk assessment of information and telecommunications networks. The aim is to reduce the potential losses caused by the risks of information and telecommunications network (ITN) functioning by taking timely risk management measures. The objectives are: classification of ITN risks, highlighting the main factors and causes of their occurrence; formation of a systematic presentation of risks to identify their manifestation and consequences; development of the method for assessing the influence of the risk and private risk on probable consequences; obtaining a quantitative risk assessment of ITN. The methods used are: system analysis of risks, method of cognitive maps, cause-and-effect analysis. The following results are obtained: classification of private risks of ITN according to the reasons and the factors of their occurrence is made; the negative consequences affecting the basic characteristics of the operation of ITN are defined; as a result, the structural system model of ITN risks is formed, in which the relationships between the elements of the main aspects of risk are shown; the method based on the theory of causal analysis is suggested in order to quantify the risk impact on ITN functioning. The risk model is based on the construction and analysis of probabilistic or fuzzy cognitive maps. Experts estimate the level of influence of private risks on the characteristics of the network in order to make decisions on risk management. The generalized structure of the cause-effect diagram of the risk factors, manifestation and consequences is developed; on ITN basis the method for quantifying the probability of risk consequences is suggested. The quantitative assessment of probable malfunctioning of the network that is determined by a specific effect (taking into account ITN probability), which is caused by private risks is also made. Conclusion.The suggested approach for quantitative assessment of ITN risk is based on the method of cause-and-effect analysis and enables taking into account both the factors causing it and probable consequences. The obtained results can be used to determine probable failures and losses in ITN functioning on the basis of the information about the degree of risk factors effects, risk events and consequences, and the cause-effect relationships between them. Thus, potential losses can be identified; measures to manage the risks of ITN functioning can be taken. K e ywor d s : information-telecommunication network, risk factors, consequences, cause-effect diagram, influence factors.

This paper considers a model of object detection on aerial photographs and video using a neural network in unmanned aerial systems. The development of artificial intelligence and computer vision systems for unmanned systems (drones, robots) requires the improvement of models for detecting and recognizing objects in images and video streams. The results of video and aerial photography in unmanned aircraft systems are processed by the operator manually but there are objective difficulties associated with the operator’s processing of a large number of videos and aerial photographs, so it is advisable to automate this process. Analysis of neural network models has revealed that the YOLOv5x model (USA) is most suitable, as a basic model, for performing the task of object detection on aerial photographs and video. The Microsoft COCO suite (USA) is used to train this model. This set contains more than 200,000 images across 80 categories. To improve the YOLOv5x model, the neural network was trained with a set of VisDrone 2021 images (China) with the choice of such optimal training parameters as the optimization algorithm SGD; the initial learning rate (step) of 0.0005; the number of epochs of 25. As a result, a new model of object detection on aerial photographs and videos with the proposed name VisDroneYOLOv5x was obtained. The effectiveness of the improved model was studied using aerial photographs and videos from the VisDrone 2021 set. To assess the effectiveness of the model, the following indicators were chosen as the main indicators: accuracy, sensitivity, the estimation of average accuracy. Using a convolutional neural network has made it possible to automate the process of object detection on aerial photographs and video in unmanned aerial systems.

In the past twenty years or so, three approaches to brand portfolio management strategies have emerged. The first approach is marketing. This approach is associated with building a corporate brand portfolio. The goal is to increase diversified cash flows by entering new market segments. The second approach is related to the competitive strategy of the enterprise. A false portfolio of intellectual property applications is being created. Competitors are expected to spend resources in retaliation. The third approach is the formation of a dynamic strategy for investment portfolio management. Due to the complex structure of the modern global financial market, the heterogeneous structure of available financial instruments and traders using different approaches and time horizons, forecasts, as a rule, require a large number of observations, work poorly in the vicinity of bifurcations and do not have a computer model that could build forecasts in real time. In such structures, slow diffusion-type processes with the phenomenon of memory arise, that is, non-Markov processes. Moreover, such structures can have fractal properties. In this work, it seems to us, the first step has been taken to build a "synthetic" model of dynamic asset portfolio management. By analyzing the data available in the scientific literature, a mathematical model of strategic brand portfolio management is proposed. In view of the above, the model has the form of a differential equation in fractional derivatives. In connection with the risk analysis, two models of fractional entropy are also considered - fractional Kolmogorov-Sinai entropy and fractional Shannon entropy.

The subject of the article is the use of industrial clusters as tools for innovative economic growth. The purpose of the article is to develop an economic-mathematical model of the formation of an industrial cluster, and to create an algorithm for cluster zoning of the economy. Tasks to be solved – analysis of the principles of innovative growth, development of a model of an innovation-engineering industrial cluster, formulation of a methodology for the formation of a regional innovation-engineering cluster, analysis and assessment of the features that arise in clusters, use of cluster analysis for systematization, classification and reduction of the number of features. Applied methods: system analysis, project approach, institutional theory, clustering methods, Bartlett’s sphericity criterion and Kaiser–Meyer–Olkin sampling adequacy criterion, multivariate regression analysis, Fisher’s F-test. The results obtained: it was determined that the best approach to unification of the main components of innovative development, namely state bodies, business and development institutes, is the creation of innovation and engineering clusters. The principles of creation and functioning of such clusters are described. It is shown that the basis of the cluster construction algorithm of regions is the integration of quantitative and qualitative methods of identification and clustering of the economy. This makes it possible, in contrast to existing approaches, not only to identify cluster elements, but also to model the levels of interaction between them. It is proposed to use the synergistic effect from the use of the newly formed structure as an assessment of the efficiency of the cluster. Conclusions: the use of regional innovation and engineering clusters allows for the formation of an effective strategy for the development of the region’s economy. The developed algorithm of cluster zoning integrates quantitative and qualitative methods of determining the clustering possibilities of the region’s economy. The complex interaction of economic and political factors leads to a synergistic effect and allows modeling cluster formation with the identification of the composition of participants and the level of interaction between them.