Сучасні інформаційні системи

Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/62915

У журналі публікуються результати досліджень з експлуатації та розробки сучасних інформаційних систем у різних проблемних галузях.

Рік заснування: 2017. Періодичність: 4 рази на рік. ISSN 2522-9052 (Print)

Новини

Включений до "Переліку наукових фахових видань України, в яких можуть публікуватися результати дисертаційних робіт на здобуття наукових ступенів доктора і кандидата наук" (технічні науки) наказом Міністерства освіти і науки України від 04.04.2018 № 326 (додаток 9, п. 56).

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Assessing and forecasting the state of deteriorating systems with the use of modified regression polynomials on the basis of functional approximation of their coefficients
(Національний технічний університет "Харківський політехнічний інститут", 2023) Raskin, Lev; Sukhomlyn, Larysa; Sokolov, Dmytro; Vlasenko, Vitalii
Object of research is technical state of deteriorating systems whose operating conditions depend on a large number of interacting factors. The caused inhomogeneity of the sample of initial data on the technical state leads to impossibility of correct use of traditional methods of assessing the state of a system (meaning methods using mathematical tools of regression analysis). Subject of research is developing a method for constructing a regression polynomial based on the results of processing a set of controlled system parameters. Non-linearity of the polynomial describing the evolution of the technical state of real systems leads to an increase in the number of regression polynomial coefficients subject to estimation. The problem is further complicated by the growing number of factors affecting the technical state of the system. In these circumstances, the so-called occurs. Goal the research consists in developing a method for constructing an approximation polynomial that describes evolution of the system state in a situation where the volume of the initial data sample is insufficient for correct estimating coefficients of this polynomial. The results obtained. The paper proposes a method for solving the given problem, based on implementation of a two-stage procedure. At the first stage a functional description of the approximation polynomial coefficients is performed; and this radically reduces the number of regression polynomial parameters to be estimated. This polynomial is used for preliminary estimation of its coefficients with the aim of filtering out insignificant factors and their interactions. At the second stage, parameters of the truncated polynomial are estimated by means of using standard technologies of mathematical statistics. Two approaches to constructing a modified polynomial have been studied: the additive one and the multiplicative one. It has been shown that the additive approach is, on average, an order of magnitude more effective than the multiplicative one.
Diagnosis of systems under conditions of small initial data sampling
(Національний технічний університет "Харківський політехнічний інститут", 2023) Raskin, Lev; Karpenko, Viacheslav; Ivanchykhin, Yuriy; Sokolov, Dmitro
Object of the study is to assess systems state in conditions of a small sample of initial data. Relevance of the problem is as follows. The functioning of a significant number of real objects takes place under conditions of poorly predicted changes in the values of environmental factors affecting system efficiency. The resulting heterogeneity of the results of objects experimental study and the environment of their functioning leads to reduction in sample size. At the same time, the standard requirements regarding the correspondence of the number of experiments and the number of coefficients of regression equation determining system state are not met. Purpose of the study is to develop methods for assessing systems state operating in a changing environment, in conditions of small sample of initial data. Tasks to be solved to achieve the goal: the first is the equivalent transformation of the set of observed initial data forming a passive experiment in aggregate into an active experiment, which corresponds to an orthogonal plan; the second is the construction of a truncated orthogonal representative sub-plan of the general orthogonal plan obtained as a result of solving the first problem. Research methods: statistical methods of experimental data processing, regression analysis, method for solving a triaxial boolean assignment problem. The results obtained: orthogonal representative subplan of the complete factorial experiment being formed makes it possible to calculate a truncated regression equation containing all the influencing factors and their interactions. Analysis of the coefficients of this equation by known methods makes it possible to cut off its insignificant elements.
Multi-criteria evaluation of the multifactor stochastic systems effectiveness
(Національний технічний університет "Харківський політехнічний інститут", 2023) Raskin, Lev; Sukhomlyn, Larysa; Sokolov, Dmytro; Vlasenko, Vitalii
Subject of the research in the article is the evaluation of complex multifactor stochastic systems functioning effectiveness according to a variety of correlated criteria. The problem actuality is determined by the fact that an independent evaluation of system effectiveness for each of the mutually correlated criteria for the system under consideration is not informative. In well-known works in the direction of multiple correlation, a relatively simple problem of estimating the correlation between one resulting parameter and a set of influencing factors is considered, which is not enough for the analysis and management of multicriteria systems. In addition, the known results do not take into account possible significant differences in influencing factors mutual cor relation values. Purpose of Work is to develop a methodology for a comprehensive assessment of system effectiveness according to a variety of interrelated criteria. Tasks to be Solved: splitting the set of system parameters into two subsets (parameters determining the effectiveness of system and parameters affecting it), forming additive convolutions of parameters included in subsets, developing a methodology for calculating the multiple correlation coefficient between the components of the selected subsets, developing a method for differentiating a scalar function from a vector argument by this argument. Applied Methods: nonlinear programming, multidimensional correlation analysis, method of differentiation of scalar functions by vector argument. These methods are used for forming and calculating a multiple correlation coefficient between the set of system effectiveness complex criterion components values and its control parameters set values. Results Obtained: proposed methodology provides the possibility of solving the problems of system management, taking into account the revealed relationship between the multi-criteria evaluation of system effectiveness and values of its controlled parameters. At the same time, an important advantage of the obtained result lies in the possibility that arises when using it to take into account the joint (group) influence of control variables on the complex criterion of system efficiency. The developed technology of scalar functions differentiation by vector argument has great practical importance which expands the arsenal of computational mathematics.
Evaluation of system controlled parameters informational importance, taking into account the source data inaccuracy
(Національний технічний університет "Харківський політехнічний інститут", 2023) Raskin, Lev; Sukhomlyn, Larysa; Sokolov, Dmytro; Vlasenko, Vitalii
The purpose of the study is to improve the standard methodology for controlled parameters information value assessing. The proposed method is based on the controlled parameters value probabilities analysis falling into the subintervals of the interval of possible values for different states of the system. When the value of the controlled parameter falls into the left or right boundary subintervals of the compatibility interval for any state of the object, the conclusion about its state is made taking into account possible errors of the first or second kind in this case. When the controlled parameter value enters the central subinterval, useful information appears if the corresponding probabilities for the states H₁ and H₂ are differ significantly. Thus, it is shown that taking into account the probabilities of fuzzy values of the controlled parameter falling into the compatibility interval for various states of the object significantly increases its informational value.
Evaluation model of the recovery processes of non-markovian systems, considering the elements unreliability under arbitrary distribution laws
(Національний технічний університет "Харківський політехнічний інститут", 2022) Raskin, Lev; Ivanchikhin, Yuriy; Sukhomlyn, Larysa; Svyatkin, Iaroslav; Korsun, Roman
The subject of the study is the reliability of recoverable non–Markovian systems, functioning of which is described by arbitrary distribution laws. The purpose of the article is to develop a mathematical model of the functioning of modern computer systems under arbitrary laws of the distribution of stay duration in each of the states, taking into account the recovery system and the provision of spare elements. The main task is to develop an adequate model of the system functioning process, taking into account the non-Markovian character of the processes occurring in the system, its possible large dimension, and the presence of a hierarchical recovery system. Based on this model, a method for calculating the density of the system recovery time distribution has been developed. At the same time, a universal four-parameter distribution is proposed to describe random processes occurring in the system. Using this approximation, the calculation of the desired parameter of the recovery flow is performed by solving the Volterra integral equation with a difference kernel.
Analysis of marсovian systems with a given set of selected states
(Національний технічний університет "Харківський політехнічний інститут", 2022) Raskin, Lev; Sukhomlyn, Larysa; Korsun, Roman
Analysis of stationary Marcovian systems is traditionally performed using systems of linear Kolmogorov differential equations. Such systems make it possible to determine the probability of the analyzed system being in each of its possible states at an arbitrary time. This standard task becomes more complicated if the set of possible states of systems is heterogeneous and some special subset can be distinguished from it, in accordance with the specifics of the system functioning. Subject of the study is technology development for such systems analysis. In accordance with this, the purpose of the work is to find the distribution law of the random duration of such a system's stay on a set of possible states until it falls into a selected subset of these states. Method for solving the problem is proposed based on splitting the entire set of possible states of the system into two subsets. The first of them contains a selected subset of states, and the second contains all the other states of the system. Now a subset of states is allocated from the second subset, from which a direct transition to the states of the first subset is possible. Next, a system of differential equations describing the transitions between the formed subsets is formed. The solution of this system of equations gives the desired result – distribution of the random duration of the system's stay until the moment of the first hit in the selected subset of states. The method allows solving a large number of practical problems, for example, in the theory of complex systems reliability with many different failure states. In particular, finding the law of the uptime duration distribution, calculating the average duration of uptime.
Semi-Markov reliability models
(Національний технічний університет "Харківський політехнічний інститут", 2022) Raskin, Lev; Sviatkin, Iaroslav; Ivanchikhin, Yuriy; Korsun, Roman
Traditional technologies for reliability analysis of semi-Markov systems are limited to obtaining a stationary state probability distribution. However, when solving practical control problems in such systems, the study of transient processes is of considerable interest. This implies the subject of research - the analysis of the laws of distribution of the system states probabilities. The goal of the work is to obtain the desired distribution at any time. The complexity of the problem solving is determined by the need to obtain a result for arbitrary distribution laws of the duration of the system's stay in each state before leaving. An easy-to-implement method for the analysis of semi-Markov reliability models has been suggested. The method is based on the possibility of approximating probability-theoretic descriptions of failure and recovery flows in the system using the Erlang distribution laws of the proper order. The developed computational scheme uses the most important property of Erlang flows, which are formed as a result of sieving the simplest Poisson flow. In this case, the semi-Markov model is reduced to the Markov one, which radically simplifies the analysis of real systems.