2024

Постійне посилання на фонд

https://ela.kpi.ua/handle/123456789/71007

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Проекція градієнта: спрощення області мінімізації афінним перетворенням
(КПІ ім. Ігоря Сікорського, 2024) Спекторський, І. Я.
Розглянуто класичну задачу оптимізації у скінченновимірному просторі, тобто знаходження мінімуму функції на непорожній множині. Пошук точного розв’язку цієї задачі аналітичними методами потребує множинних обчислювальних ресурсів або взагалі неможливий. Для реальних задач частіше застосовують методи пошуку наближеного розв’язку, серед яких одним з найпростіших і найвідоміших для задач безумовної оптимізації є метод градієнтного спуску. Узагальненням методу градієнтного спуску на випадок умовної оптимізації є запропонований у 1964 р. метод проекції градієнта. Для деяких типів множини (відрізок, паралелепіпед, куля) проекцію точки на множину можна знайти простими явними формулами, проте для складніших (напр., еліпс) проектування стає окремою задачею мінімізації. Однак у деяких випадках обчислення проекції не можна спростити афінним перетворенням — напр., еліпс афінним (і навіть лінійним) перетворенням можна звести до кулі. Спрощено задачу мінімізації функції на множині застосуванням афінного перетворення F(x) = Ax+b, де A — невироджена квадратна матриця, b — фіксований вектор відповідної розмірності.
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Decentralized leader-following con-sensus control design for discrete-time multi-agent systems with switching to-pology
(КПІ ім. Ігоря Сікорського, 2024) Dorofieiev, Y. I.; Lyubchyk, L. M.; Malko, M. M.
The problem of consensus control of linear discrete-time multi-agent systems (MASs) with switching topology is considered in the presence of a leader. The goal of consensus control is to bring the states of all agents to the leader state while providing stability for local agents, as well as the MAS as a whole. In contrast to the traditional approach, which uses the concept of an extended dynamic multi-agent system model and communication topology graph Laplacian, this paper proposes a decomposition approach, which provides a separate design of local controllers. The control law is chosen in the form of distributed feedback with discrete PID controllers. The problem of local controllers’ design is reduced to a set of semidefinite programming problems using the method of invariant ellipsoids. Sufficient conditions for agents’ stabilization and global consensus condition fulfillment are obtained using the linear matrix inequality technique. The availability of information about a finite set of possible configurations between agents allows us to design local controllers offline at the design stage. A numerical example demonstrates the effectiveness of the proposed approach.
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Study of the factor influence on the uniformity of coffee grain grinding by methods of sta-tistical analysis
(КПІ ім. Ігоря Сікорського, 2024) Hryhorenko, I. V.; Kondrashov, S. I.; Hryhorenko, S. M.; Opryshkin, O. S.
In order to assess the impact of each of the factors that affect the quality and uniformity of grinding coffee beans and to compare the impact of these factors, it is worth establishing a quantitative indicator of this impact. To solve this problem, dispersion analysis was used as a method of organizing sample data according to possible sources of dispersion. The chosen method made it possible to decompose the total dispersion into components caused by the influence of factor levels. Grinding time, geometric dimensions of the grain, moisture content of the grain, speed of rotation of the motor shaft were selected as factors influencing the homogeneity of grinding. The justification and assessment of the reliability of statistical conclusions about the informational significance of indicators affecting the homogeneity of coffee grinding was carried out to ensure the highest possible probability of the obtained result.
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Expansion of the mathematical apparatus of discrete-continuous networks for the automation of their synthe-sis procedures
(КПІ ім. Ігоря Сікорського, 2024) Gurskiy, A. A.; Denisenko, A. V.; Goncharenko, A. E.
The paper deals with a model of an intelligent system related to the automatic synthesis of Petri nets and presents a certain stage of developing this model. The peculiarity of the extended mathematical apparatus is that it contains a combination of Petri net incidence matrices to represent various algorithms. This combination of matrices is part of the equations describing the logic control device of a complex system. Accordingly, the work also presents a well-known mathematical description of discrete-continuous systems with a controlled structure, which includes certain logical control devices. This mathematical description, based on means of discrete-continuous networks, is associated with the incidence matrix of the Petri net, which is formed as a result of a particular synthesis algorithm. At the same time, the formed Petri net represents the corresponding logical control algorithm that should ensure the effective functioning of the corresponding system. The final part of the work presents various structural schemes of logic-dynamic models of systems related to the automatic synthesis of Petri nets. Here, we determine the features of the advanced mathematical apparatus based on discrete-continuous networks to develop an intelligent system that forms logical control algorithms. It is also noted that such systems can be used to create certain control algorithms that ensure increased efficiency of the functioning of some objects in difficult and unpredictable conditions.
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Polarization-based target detection approach to enhance small surface object identification ensuring navigation safety
(КПІ ім. Ігоря Сікорського, 2024) Stetsenko, M.; Melnyk, O.; Vorokhobin, I.; Korban, D.; Onishchenko, O.; Ternovsky, V.; Ivanova, I.
This research introduces a groundbreaking approach to significantly enhance the performance of navigation radars under adverse weather conditions. Traditional ship radars, relying on horizontal polarization, encounter difficulties in effectively suppressing rain interference. In response, this study proposed an innovative method employing circular polarization for detecting navigation targets. This technique capitalizes on the distinct polarization properties exhibited by stable navigation targets and fluctuating interfering objects. Theoretical analysis and model experiments substantiate consistent ellipticity parameter values of scattered waves, independent of rain intensity, for both rain interferers and surface metallic objects. The practical implications of our research are highly promising. They enable detection irrespective of the noise-to-signal ratio by integrating an additional channel of circularly polarized waves and applying straightforward mathematical functions. This advancement marks a significant stride towards overcoming the challenges posed by rainy conditions in maritime navigation radar systems.
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Multi-factor forecasting of statistical trends for Data Science problems
(КПІ ім. Ігоря Сікорського, 2024) Pysarchuk, O.; Andreieva, T.; Grinenko, O.; Baran, D.
The article deals with the processes of multi-factor forecasting of statistical trends for Data Science problems. Most of the classic approaches to data processing consist of studying the consequences of phenomena rather than the factors of their appearance. At the same time, the factors affecting the behavior of the investigated process are assumed to be random and are not investigated. The article discusses the approach to forecasting the parameters of the trend of statistical time series, which consists of the study of factors that lead to changes in the dynamics of the studied process. This approach potentially has better indicators of adequacy, accuracy, and efficiency in obtaining final solutions than classical approaches. The implementation of this approach is shown using an example of the analysis of exchange rate changes. The obtained results show the practicality of considering multifactoriality in forecasting tasks.
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Strategy of the cyber-physical system for the small business enterprise guaranteed functioning with the digi-tal twin support
(КПІ ім. Ігоря Сікорського, 2024) Pankratova, N. D.; Tymchik, G. S.; Pankratov, Ye. V.
The article presents a strategy of the cyber-physical system guaranteed functioning for a small business enterprise (SBE), which is ensured by maintaining the digital twin and is due to its extremely high relevance in modern conditions. Business processes are linked to Industry 4.0 competencies. One of the innovations it implements is Digital Twin, a comprehensive facility support tool. Digital twin allows for tracking and effectively managing the entire cycle of an infrastructure project, from planning, procurement, and production to commissioning and maintenance of the facility. PEST, SWOT, SAW, TOPSIS, and VIKOR methods are used to build a strategy.
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A hybrid model of artificial intelligence integrated into GIS for predicting accidents in water supply networks
(КПІ ім. Ігоря Сікорського, 2024) Zaychenko, Yu.; Starovoit, T.
The search for an effective and reliable model for predicting accidents on water supply networks by determining their exact locations has always been important for effectively managing water distribution systems. This study, based on the adaptive neuro-fuzzy logical inference system (ANFIS) model, was developed to predict accidents in the city of Kyiv (Ukraine) water supply network. The ANFIS model was combined with genetic algorithms and swarm optimization (ACO) methods and integrated into a GIS to visualize results and determine locations. Forecasts were evaluated according to the following criteria: mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2 ). Depending on the amount and type of input data, ANFIS optimization with genetic algorithms and swarm optimization (ACO) can, on average, increase the accuracy of ANFIS predictions by 10.1% to 11%. The obtained results indicate that the developed hybrid model may be successfully applied to predict accidents on water supply networks.
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Interactive decision support system for lung cancer segmentation
(КПІ ім. Ігоря Сікорського, 2024) Sydorskyi, V.
This paper studies Clinical Intelligent Decision Support Systems (CIDSSs) for lung cancer segmentation, which are based on deep neural nets. A new interactive CIDSS is proposed and compared with previous approaches. Additionally, the purpose uncertainty problem in building interactive systems is discussed, and criteria for measuring both quality and amount of user feedback are proposed. In order to automate system evaluation, a new algorithm was used to simulate expert feedback. The proposed interactive CIDSS outperforms previous approaches (both interactive and noninteractive) on the task of lung lesion segmentation. This approach looks promising both in terms of quality and expert user experience. At the same time, this paper discusses a bunch of possible modifications that can be done to improve both evaluation criteria and proposed CIDSS in future works.
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An improved approach to organising mobile edge computing in a 5G network
(КПІ ім. Ігоря Сікорського, 2024) Аstrakhantsev, А.; Globa, L.; Fedorov, О.; Degtiarov, D.; Romanko, Y.; Romanii, K.
Mobile edge computing is an important element in ensuring the efficiency of the 5G network as a whole, as it enables data storage and computing at the network edge. Existing solutions do not fully address the issues of load distribution between computing nodes, and most solutions do not offer methods for verifying computations and controlling errors. Accordingly, this paper aims to develop an approach to the organization of mobile edge computing in a 5G mobile network that would authenticate distribution servers and computing nodes, manage the process of distributing computing nodes, have a procedure for verifying the correctness of calculations, and take into account the parameters of computing nodes during distribution. To achieve this goal, we propose to use the developed method. The method of load balancing and selection of computing nodes for edge computing via 5G allows for identifying available nodes and distributing computing blocks among them. It also provides mutual authentication of elements and includes a method of data verification and error detection for the MEC system. The provided solution allows for controlling errors during calculations and protecting the server from incorrect data. These methods are optimized according to minimum network resources and computing time criteria. These improvements increase the efficiency of mobile edge computing in a 5G network.
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Improving the accuracy of neural network exchange rate forecasting using evolutionary modeling method
(КПІ ім. Ігоря Сікорського, 2024) Fedin, S. S.
A set ofmodels of feedforward neural networks is created to obtain op-erational forecasts of the time series of the hryvnia/dollar exchange rate. It is shown that using an evolutionary algorithm for the total search of basic characteristics and a genetic algorithm for searching the values of the matrix of neural network weight coefficients allows optimizing the configuration and selecting the best neural net-work models according to various criteria of their training and testing quality. Based on the verification of forecasting results, it is established that the use of neural net-work models selected by the evolutionary modelling method increases the accuracy of forecasting the hryvnia/dollar exchange rate compared to neural network models created without the use of a genetic algorithm. The accuracy of the forecasting re-sults is confirmed by the method of inverse verification using data from different retrospective periods of the time series using the criterion of the average absolute percentage error of the forecast
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Determination of the generalized optimality criteria for selecting civilian shelter facilities from attacks by ballistic (cruise) missiles and kamikaze drones in urbanized areas
(КПІ ім. Ігоря Сікорського, 2024) Yakovenko, V.; Furmanova, N.; Flys, I.; MalyiI, O.; Farafonov, O.; Moroz, H.
The object of the study is the planning of the selection of civilian shelter from attacks by ballistic (cruise) missiles and kamikaze drones in urbanized areas. A generalized model for assessing the choice of civilian shelter facilities has been developed by applying linear forms of factor linkage in combination with a general-ized optimality criterion in the form of a linear combination of local criteria. The multivariate regression analysis method was chosen to study the correlation between the generalized criterion and the observed feature. A generalized criterion for the op-timal choice of civilian shelter facilities from attacks by ballistic (cruise) missiles and kamikaze drones in urbanized areas is calculated in the form of regression coef-ficients. The criterion can facilitate a simplified determination of the generalized in-dicator of a linear model for planning the protection of civilians in cities outside the area of hostilities. The initial data is a set of physical (technical) states of shelters with a list of values and features sufficient to assess their resistance to high dynamic loads
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The role of generative artificial intelligence (gai) in scientific research
(КПІ ім. Ігоря Сікорського, 2024) Petrenko, Anatolii
The emergence and growing capabilities of Generative Artificial Intelli-gence (GAI) are profoundly transforming scientific research. Although AI extends human intelligence by automating certain tasks, it complements rather than replaces human creativity. This article discusses the implications of AI for the scientific process, including ethical considerations and the need for a balanced approach that combines the strengths of human and artificial intelligence in the process of discov-ering knowledge and solving complex problems. The discussion extends to the need for universities to adapt their curricula to prepare future researchers for the AI era, emphasizing scenario-based thinking and uncertainty management as important skills for the future.
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Generalized scenarios of transition to chaos in ideal dynamic systems
(КПІ ім. Ігоря Сікорського, 2024) Horchakov, Oleksii; Shvets, Aleksandr
The implementation of a new scenario of transition to chaos in the classi-cal Lorenz system has been discovered. Signs of the presence of an implementation of the generalized intermittency scenario for dynamic systems are described. Phase-parametric characteristics, Lyapunov characteristic exponents, distributions of in-variant measures, and Poincaré sections are constructed and analyzed in detail, which confirm the implementation of the generalized intermittency scenario in an ideal Lorenz system
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Fairness of 2d corotational beam spline as compared with geometrically nonlinear elastic beam
(КПІ ім. Ігоря Сікорського, 2024) Orynyak, Igor; Yablonskyi, Petro; Koltsov, Dmytro; Chertov, Oleg; Mazuryk, Roman
The goal of this paper is to further investigate the properties and advan-tages of corotational beam spline, CBS, as suggested recently. Emphasis is placed on the relatively simple task of drawing the spline between two endpoints with pre-scribed tangents. In the capacity of “goodness” of spline, the well-known notion of “fairness” is chosen, which presents itself as the integral from the squared curvature of spline over its length and originates from the elastic beam theory as the minimum of energy of deformation. The comparison is performed with possible variants of the cubic Bezier curve, BC, and geometrically nonlinear beam, GNB, with varying lengths. It was shown that CBS was much more effective than BC, where any at-tempt to provide better fairness of BC by varying the distances from endpoints to two intermediate points generally leads to lower fairness results than CBS. On the other hand, GNB, or in other words, the elastica curve, can give slightly better val-ues of fairness for optimal lengths of the inserted beam. It can be explained by the more sophisticated scientific background of GNB, which employs 6 degrees of free-dom in each section, compared with CBS, which operates only by 4 DoF
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Reducing risk for assistive reinforcement learning policies with diffusion models
(КПІ ім. Ігоря Сікорського, 2024) Tytarenko, Andrii
Care-giving and assistive robotics, driven by advancements in AI, offer promising solutions to meet the growing demand for care, particularly in the context of increasing numbers of individuals requiring assistance. It creates a pressing need for efficient and safe assistive devices, particularly in light of heightened demand due to war-related injuries. While cost has been a barrier to accessibility, techno-logical progress can democratize these solutions. Safety remains a paramount con-cern, especially given the intricate interactions between assistive robots and humans. This study explores the application of reinforcement learning (RL) and imitation learning in improving policy design for assistive robots. The proposed approach makes the risky policies safer without additional environmental interactions. The enhancement of the conventional RL approaches in tasks related to assistive robotics is demonstrated through experimentation using simulated environments.
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Identification of nonlinear systems with periodic external actions (part I)
(КПІ ім. Ігоря Сікорського, 2024) Gorodetsky, Viktor
The problem of identifying nonlinear systems with periodic external ac-tions is considered in the article. The number of such actions in the system is not limited, and these actions can be either additive or multiplicative. We use a time se-ries of observed system variables to calculate unknown equation coefficients. The proven theorem allows us to separate the unknown coefficients of the system into variables and constants. The proposed computational procedure allows us to avoid possible errors caused by the discrete nature of observable time series. Identification of zero coefficients is carried out in two ways, eliminating erroneous zeroing of the terms of the equations. The method is illustrated with a numerical example of identi-fying a chaotic system with periodic external actions
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Data scrambler knight tour algorithm
(КПІ ім. Ігоря Сікорського, 2024) Romanuke, V. V.; Yaremko, S. A.; Kuzmina, O. M.; Yehoshyna, H. A.
Nowadays, data scrambling remains a vital technique to protect sensitive information by shuffling it in a way that makes it difficult to decipher or reverse-engineer while still maintaining its usability for legitimate purposes. As manipulat-ing the usability of the scrambled data remains a challenge on the background of risking losing data and getting them re-identified by attackers, scrambling and de-scrambling should be accomplished faster by not increasing data loss and re-identification risks. A scrambling algorithm must have a linear time complexity, still shuffling the data to minimize the risks further. A promising approach is based on the knight open tour problem, whose solutions appear like a random series of knight positions. Hence, a knight open tour algorithm is formalized, by which the knight seems to move chaotically across the chessboard. The formalization is presented as an indented pseudocode to implement it efficiently, whichever programming lan-guage is used. The output is a square matrix representing the knight open tour. Based on the knight tour matrix, data scrambler and descrambler algorithms are pre-sented in the same manner. The algorithms have a linear time complexity. The knight-tour scrambling has a sufficiently low guess probability if an appropriate depth of scrambling is used, where the data is re-scrambled repetitively. The scram-bling depth is determined by repetitive application of the chessboard matrix, whose size usually increases as the scrambling is deepened. Compared to the pseudoran-dom shuffling of the data along with storing the shuffled indices, the knight-tour de-scrambling key is stored and sent far simpler yet ensures proper data security.
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Comparison of methods for interpolation and extrapolation of boundary trajectories of short-focus electron beams using root-polynomial functions
(КПІ ім. Ігоря Сікорського, 2024) Melnyk, Igor V.; Pochynok, Alina V.; Skrypka, Mykhailo Yu.
The article considers and discusses the comparison of interpolation and extrapolation methods of estimation of the boundary trajectory of electron beams propagated in ionized gas. All estimations have been computed using root-polynomial functions to numerically solve a differential-algebraic system of equa-tions that describe the boundary trajectory of the electron beam. By providing analy-sis, it is shown and proven that in the case of solving a self-connected interpolation-extrapolation task, the average error of the beam radius estimation is generally smaller. This approach was especially effective in estimating the focal beam radius. An algorithm for solving self-connected interpolation-extrapolation tasks is given, and its efficiency is explained. Corresponding graphic dependencies are also given and analyzed
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Intelligent optimal control of nonlinear diabetic population dynamics system using a genetic algorithm
(КПІ ім. Ігоря Сікорського, 2024) El Ouissari Abdellatif; El Moutaouakil Karim
Diabetes is a chronic disease affecting millions of people worldwide. Several studies have been carried out to control the diabetes problem, involving both linear and non-linear models. However, the complexity of linear models makes it impossible to describe the diabetic population dynamic in depth. To capture more detail about this dynamic, non-linear terms were introduced into the mathematical models, resulting in more complicated models strongly consistent with reality (capable of re-producing observable data). The most commonly used methods for control estimation are Pantryagain’s maximum principle and Gumel’s numerical method. However, these methods lead to a costly strategy regarding material and human resources; in addition, diabetologists cannot use the formulas implemented by the proposed controls. In this paper, the authors propose a straightforward and well-performing strategy based on non-linear models and genetic algorithms (GA) that consists of three steps: 1) discretization of the considered non-linear model using classical numerical methods (trapezoidal rule and Euler–Cauchy algorithm); 2) estimation of the optimal control, in several points, based on GA with appropriate fitness function and suitable genetic operators (mutation, crossover, and selection); 3) construction of the optimal control using an interpolation model (splines). The results show that the use of the GA for non-linear models was successfully solved, resulting in a control approach that shows a significant decrease in the number of diabetes cases and diabetics with complications. Remarkably, this result is achieved using less than 70% of available resources.