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“Informatics and Applications” scientific journalVolume 17, Issue 1, 2023Content Abstract and Keywords About Authors ANALYTICAL MODELING OF DISTRIBUTIONS WITH INVARIANT MEASURE IN STOCHASTIC SYSTEMS WITH UNSOLVED DERIVATIVES
Abstract: Exact and approximate analytical modeling methods for stochastic processes with invariant measure in Gaussian and non-Gaussian stochastic systems with unsolved derivatives are considered. The methods are based on the linear regression approximation of nonlinear functions with unsolved derivatives and reduction to stochastic Ito differential equations. Two exact methods for analytical modeling of one- and multidimensional distributions with invariant measure are described. Special attention is paid to normal approximation and parametrization methods. A test example for Duffing equation nonlinear in second derivative is given. The stationary and nonstationary regimes and asymptotic stability are investigated. The method of normal approximation for one- and two-dimensional distributions is accurate enough for engineering applications. Some generalizations concerning numerical analytical modeling are considered. Keywords: analytical modeling; distribution parametrization; distribution with invariant measure; stochastic system; stochastic system with unsolved derivatives; stochastic process AN AXIOMATIC VIEWPOINT ON THE ROGERS-VERAART AND SUZUKI-ELSINGER MODELS OF SYSTEMIC RISK
Abstract: The authors study a model of clearing in an interbank network with crossholdings and default charges. Following the Eisenberg-Noe approach, the authors define the model via a set of natural financial regulations including those related to eventual default charges and derive a finite family of fixpoint problems. These problems are parameterized by vectors of binary variables. The model combines features of the Ararat-Meimanjanov, Rogers-Veraart, and Suzuki-Elsinger networks. The authors develop methods of computing the maximal and minimal clearing pairs using the mixed integer-linear programming and a Gaussian elimination algorithm. Keywords: systemic risks; financial networks; clearing; crossholdings; default charges TESTS FOR NORMALITY OF THE PROBABILISTIC DISTRIBUTION WHEN DATA ARE ROUNDED
Abstract: Tests for normality are less sensitive to the data rounding than, for example, tests for exponentiality but among normality tests, the sensitivity is very different. In this paper, the authors find out which tests are more and which ones are less sensitive. The authors show that tests based on sample moments are much more robust with respect to the data rounding than tests based on order statistics (in contrast to the robustness with respect to outliers where order statistics are more robust than sample moments). This, however, only applies to the probability of Type I error. The probability of Type II error is very insensitive to the data rounding for all normality tests. Keywords: normal distribution; test for normality; rounded data; significance level; Monte-Carlo simulation AN AVERAGE DISTANCE IN THE POWER-LAW CONFIGURATION GRAPHS
Abstract: In random configuration graphs with a discrete power-law vertex degree distribution with a fixed parameter, the average distance in the graph is considered, i. e., the arithmetic mean of distances between all pairs of graph nodes. This characteristic is estimated using simulation methods. Due to computational constraints, the author considers graphs in the pre-asymptotic domain (in this paper, these are the graphs up to 7000 nodes). The models of dependencies of the average distance on the graph size and the parameter of vertex degree distribution are reseived. The obtained results are compared with the results of theoretical studies of the typical distance in a graph in the asymptotics (i. e., when the number of graph vertices tends to infinity), given in the works by R. Hofstad Keywords: configuration graph; power-law distribution; average distance in a graph; simulation OPTIMAL SPANNING TREE RECONSTRUCTION IN SYMBOLIC REGRESSION
Abstract: The paper investigates the problem of regression model generation. A model is a superposition of primitive functions. The model structure is described by a weighted colored graph. Each graph vertex corresponds to a primitive function. An edge assigns a superposition of two functions. The weight of an edge is equal to the probability of superposition. To generate an optimal model, one has to reconstruct its structure from its graph adjacency matrix. The proposed algorithm reconstructs the minimum spanning tree from the weighted colored graph. The paper presents a novel solution based on the prize-collecting Steiner tree algorithm. This algorithm is compared with its alternatives. Keywords: symbolic regression; linear programming; superposition; minimum spanning tree; adjacency matrix CAUSAL RELATIONSHIPS IN CLASSIFICATION PROBLEMS
Abstract: In the present paper, a classification object is considered as the cause for the appearance of one or more consequences and any classification algorithm decides on the class observing the consequences from the analyzed cause. The paper considers the consequences of the cause in the binary classification problem as sources of additional information confirming or rejecting the hypothesis of the cause in the classified object. When considering a hypothesis about the presence or absence of a certain cause in an object classified by this property, the knowledge presentation language is automatically built based on several consequences. Then, it is easy to use the available information from different information spaces in an object classification task. To use cause-and-effect relationships in a classification task, machine learning should be used. In conditions of teaching with a teacher, there are many precedents when the presence of a cause is known. Then one can statistically single out events that are the consequences of the cause. Deterministic cause-and-effect relationships generate errors only at the expense of noise. In those precedents where there is no cause, positive classification appears only at the expense of noise regardless of precedent to precedent. Thus, even a weak deviation from equally probable noise allows one to build a consistent criterion that distinguishes consequences from random noise. Sequelae can be isolated independently of each other. This follows from the determinism of the cause-and-effect relationship and the independence of noise. Keywords: finite classification task; cause-and-effect relationships; machine learning DEVELOPMENT OF A NEW MODEL OF STEP CONVOLUTIONAL NEURAL NETWORK FOR CLASSIFICATION OF ANOMALIES ON PANORAMAS
Abstract: A new model ofa stepped convolutional neural network for classifying anomalies in panoramas has been developed. Appropriate datasets for classification are selected. The conclusion is made about the incompleteness of the method previously used by the authors to find anomalies in special areas with high color difference in panoramas. The search for these areas by the previously developed method did not set the task of their classification.
Keywords: panoramic image; data set; multilabel classification; stepwise convolutional neural network; ensemble; transfer learning MODELING THE STRUCTURE OF INTEROPERABILITY BY MEANS OF STRUCTURAL CONSISTENCY
Abstract: The initial syntactic level of interoperability involves communication with the appropriate protocol, hardware, software, and necessary level of data compatibility. The work is devoted to the study of the level of compatibility of data describing interacting elements based on the feature vector. To do this, a model of structural correspondence is proposed which allows assessing the tendency to establish interoperability. Modeling structural interoperability based on the analysis of signs of connections using the introduced consistency criterion leads to finding the closest consonant pre-image to the original set. The found consonant pre-image with its subsets indicates the preferred grouping of elements in which the interoperability between them is established with the least mismatch with respect to the fixed signs of connections. Since the elements under consideration are described by a vector of parameters, from the comparison of which one can infer the similarity between the elements, respectively, the presence of elements in the same subset indicates a potential motivation for interoperability Keywords: interoperability; structural consistency; connectivity matrix FUZZY RULES BASED METHOD FOR AGENT CONFLICT MANAGEMENT IN HYBRID INTELLIGENT MULTIAGENT SYSTEMS
Abstract: The paper continues research on computer simulation with hybrid intelligent multiagent systems of a teamwork of specialists of various profiles who solve problems at a round table. The agents of such systems are autonomous software entities that imitate the reasoning of real specialists. Modeling of heterogeneous knowledge, goals, and points of view of agents on the problem posed within single intelligent system causes their collision, the emergence of conflicts by analogy with how it happens in simulated teams. Not every conflict between agents is destructive and requires suppression: conflict management in a hybrid intelligent multiagent system as well as in a team involves the identification of a decision-making situation, if necessary, stimulation and subsequent resolution of constructive forms of conflict as well as the prevention of its destructive forms. The paper proposes the method based on fuzzy rules to manage conflicts between agents in hybrid intelligent multiagent systems. Keywords: conflict; hybrid intelligent multiagent system; team of specialists; conflict management ON THE PROBLEM OF ASSESSING AND ANALYZING TRAFFIC ACCIDENTS RISK ON THE RAIL TRANSPORT
Abstract: The problem of assessing and analyzing traffic accidents risk on the rail transport is considered. Two functions of the integral risk are proposed that allow assessing danger of transportation along the entire route of a transport. The probability of an unfavorable event occurring during transportation and the expected damage are chosen as such functions. The concept of assessing probability and damage from unfavorable events during the freight trains transportation is proposed. A meaningful example of calculating integral risk functions is given on the basis of previously investigated statistics on the freight trains transportation and unfavorable events that occurred with them. Keywords: risk; unfavorable event; rail transport; probability; expected damage ESTIMATES OF THE RESOURCE DISTRIBUTION IN THE MULTIUSER NETWORK WITH EQUAL INTERNODAL LOADS
Abstract: A method for estimating resources with an equalizing distribution of internodal loads in a multiuser network is proposed. Within the framework of a formal mathematical model, the capacity of edges is considered as components of a vector of resources that are required for the transmission of different types of flows. An algorithmic procedure for the redistribution and usage of capacity with equal quota of resources for all pairs is proposed. When searching for the corresponding edge loads, the values of the maximum single-product flows for each pair of nodes are determined. In the course of computational experiments, the total resource is considered to be set for networks with various structural features. Keywords: multicommodity flow model; network resource distribution and internodal loads; network peak load OPTIMIZATION OF A QUEUE-LENGTH DEPENDENT ADDITIONAL SERVER IN THE MULTISERVER QUEUE
Abstract: The problem of optimal control of an additional server in a stationary G/M/s queue is considered.
Keywords: multiserver queuing system; optimization; additional server PREEMPTION-BASED PRIORITIZATION SCHEME FOR NETWORK RESOURCES SLICING IN 5G SYSTEMS
Abstract: The network slicing (NS) technology, which has been actively studied in recent years, is based on the representation of a common network infrastructure in the form of various customizable logical networks called slices and involves the division of mobile network operators into two groups - physical network infrastructure providers (InPs) and mobile virtual network operators (MVNOs). The MVNOs lease the physical resources of InPs to create their own slices to provide services to their users with different quality of service requirements. In the present paper, for a network with NS technology, a scheme for accessing its radio resources is proposed that provides users with services with a guaranteed bit rate (GBR) and priority control based on the implementation of the user service interruption mechanism. The authors propose a scheme for accessing radio resources of a network under NS technology that provides users with services with GBR and priority control based on the implementation of the user service interruption mechanism. To evaluate the effectiveness of the proposed scheme, a comparative analysis of its characteristics with the characteristics of the access scheme based on the resource reservation mechanism was carried out. Keywords: 5G; network slicing; quality of service; key performance indicators; priority management; service interruption; iterative method MULTIDIMENSIONAL BUTTERFLIES IN PROBLEMS OF OPTIMIZATION ON CC-VaR
Abstract: The work continues studying problems of using continuous VaR-criterion (CC-VaR) in financial markets.
Keywords: underliers; multidimensional market; investor's risk preferences function; continuous VaR-criterion; cost and forecast densities; scenario indicators; bases; binary options; one-type portfolio; market center; mixed portfolio ON THE SCIENTIFIC PARADIGM OF INFORMATICS: DATA, INFORMATION, AND KNOWLEDGE
Abstract: Three basic notions of informatics - data, information, and knowledge - are considered. The variant of specification of these notions within the framework of constructing a system of terms of the scientific paradigm of informatics as a fundamental science is proposed. On the one hand, the notions of "data," "information," and "knowledge" are widely used in the scientific literature and textbooks on informatics, in particular, when describing its theoretical foundations. On the other hand, there is still no consensus on their semantic content.
Keywords: scientific paradigm; informatics as fundamental science; data; information; knowledge; intersubjective entities of informatics; Frege's triangle
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