To provide an accurate and timely response to different types of attacks, intrusion detection systems collect and analyze a large amount of data, which may include information with limited access, such as personal data or trade secrets. Consequently, such systems can be seen as an additional source of risks associated with handling sensitive information and breaching its security. Applying the federated learning paradigm to build analytical models for attack and anomaly detection can significantly reduce such risks because locally generated data is not transmitted to any third party, and model training is done locally - on the data sources. Using federated training for intrusion detection solves the problem of training on data that belongs to different organizations, and which, due to the need to protect commercial or other secrets, cannot be placed in the public domain. Thus, this approach also allows us to expand and diversify the set of data on which machine learning models are trained, thereby increasing the level of detectability of heterogeneous attacks. Due to the fact that this approach can overcome the aforementioned problems, it is actively used to design new approaches for intrusion and anomaly detection. The authors systematically explore existing solutions for intrusion and anomaly detection based on federated learning, study their advantages, and formulate open challenges associated with its application in practice. Particular attention is paid to the architecture of the proposed systems, the intrusion detection methods and models used, and approaches for modeling interactions between multiple system users and distributing data among them are discussed. The authors conclude by formulating open problems that need to be solved in order to apply federated learning-based intrusion detection systems in practice.
This article is devoted to the problem of automation of the stage of combining wells into clusters, considered as part of the process of designing the development of oil fields. The solution to the problem of combining wells into clusters is to determine the best location of well pads and the distribution of wells into clusters, in which the costs of developing and maintaining an oil field will be minimized, and the expected flow rate will be maximized. One of the currently used approaches to solving this problem is the use of optimization algorithms. At the same time, this task entails taking into account technological limitations when searching for the optimal option for the development of an oil field, justified, among other things, by the regulations in force in the industry, namely, the minimum and maximum allowable number of wells in a pad, as well as the minimum allowable distance between two well pads. The use of optimization algorithms does not always guarantee an optimal result, in which all specified constraints are met. Within the framework of this study, an algorithm is proposed that allows us to work out the resulting design solutions in order to eliminate the violated restrictions at the optimization stage. The algorithm consistently solves the following problems: violation of restrictions on the ultra-small and ultra-large number of wells in a pad; discrepancy between the number of pads with a given one; violation of the restriction of the ultra-close arrangement of pads. To study the effectiveness of the developed approach, a computational experiment was conducted on three generated synthetic oil fields with different geometries. As part of the experiment, the quality of the optimization method and the proposed algorithm, which is a raise to the optimization method, were compared. The comparison was carried out on different values of optimization power, which denotes the maximum number of runs of the target function. The evaluation of the quality of the work of the compared approaches is determined by the amount of the fine, which indicates the degree of violation of the values of the main restrictions. The efficiency criteria in this work are: the average value, the standard deviation, the median, and the minimum and maximum values of the penalty. Due to the use of this algorithm, the value of the penalty for the first and third oil fields is reduced on average to 0.04 and 0.03 respectively, and for the second oil field, the algorithm allowed to obtain design solutions without violating restrictions. Based on the results of the study, a conclusion was made regarding the effectiveness of the developed approach in solving the problem of oil field development.
The formulation and numerical scheme for solving the problem of filtering estimates of the informational impact of mass media on the electorate, allowing with a high degree of accuracy at a given observation interval to estimate the number of individuals in society who prefer a certain political subject (opinion), are proposed in the article. A mathematical model for assessing the information impact on the electorate during election campaigns, which boils down to solving a stochastic differential equation – the equation of state, forms the basis of the formulation of the problem. When compiling a model for filtering information impact estimates, it is proposed to reduce the study of the equation of state to a numerical solution of the Duncan–Mortensen–Zakai equation by introducing an additional observation equation, which is obtained from the equation of state when evaluating its stochastic components (observed agitation intensities) by methods of polyspectral analysis. In the projection formulation of the Galerkin method, when reducing to a system of linear differential equations and obtaining its solution in a recursive estimation scheme when sampling the analysis interval into subintervals and using the matrix exponential method, the Duncan–Mortensen–Zakai equation is solved. For a visual comparison of the effectiveness of the generated numerical solution to the problem of filtering information impact assessments, calculations were carried out on test examples.
To calculate the optimal control, a satisfactory mathematical model of the control object is required. Further, when implementing the calculated controls on a real object, the same model can be used in robot navigation to predict its position and correct sensor data, therefore, it is important that the model adequately reflects the dynamics of the object. Model derivation is often time-consuming and sometimes even impossible using traditional methods. In view of the increasing diversity and extremely complex nature of control objects, including the variety of modern robotic systems, the identification problem is becoming increasingly important, which allows you to build a mathematical model of the control object, having input and output data about the system. The identification of a nonlinear system is of particular interest, since most real systems have nonlinear dynamics. And if earlier the identification of the system model consisted in the selection of the optimal parameters for the selected structure, then the emergence of modern machine learning methods opens up broader prospects and allows you to automate the identification process itself. In this paper, a wheeled robot with a differential drive in the Gazebo simulation environment, which is currently the most popular software package for the development and simulation of robotic systems, is considered as a control object. The mathematical model of the robot is unknown in advance. The main problem is that the existing mathematical models do not correspond to the real dynamics of the robot in the simulator. The paper considers the solution to the problem of identifying a mathematical model of a control object using machine learning technique of the neural networks. A new mixed approach is proposed. It is based on the use of well-known simple models of the object and identification of unaccounted dynamic properties of the object using a neural network based on a training sample. To generate training data, a software package was written that automates the collection process using two ROS nodes. To train the neural network, the PyTorch framework was used and an open source software package was created. Further, the identified object model is used to calculate the optimal control. The results of the computational experiment demonstrate the adequacy and performance of the resulting model. The presented approach based on a combination of a well-known mathematical model and an additional identified neural network model allows using the advantages of the accumulated physical apparatus and increasing its efficiency and accuracy through the use of modern machine learning tools.
The problem of the pursuit curve construction in the case when the tangent to pursuer’s motion trajectory passes at any time through the point representing the pursued is considered. A new approach to construct the pursuit curves using difference schemes is proposed. The proposed technique eliminates the need to derive the differential equations for the description of the pursuit curves, which is quite difficult task in the general case. In addition, the application of difference methods is justified in a situation where it is complicated to find the analytical solution of an existing differential equation and it is possible to obtain the pursuit curve only numerically. Various modifications of difference schemes respectively equivalent to the Euler, to the Adams – Bashforth and to the Milne methods are constructed. Their software implementation is realized by using the mathematical package Mathcad. We consider the case of a uniform rectilinear motion of the pursued whose differential equation describing the path of the pursuer and its analytical solution are known. We compare the numerical solutions obtained by the different methods with the well-known analytical solution. The error of the obtained numerical solutions is examined. Moreover, an application is considered illustrating the construction of the difference schemes for the case of an arbitrary trajectory of the pursued. Also, we extend the proposed method to the case of cyclic pursuit with several participants in the three-dimensional space. In particular, we construct a difference scheme equivalent to the Euler method for a three-dimensional analogue of the "bugs problem". The results obtained are demonstrated by means of animated examples for either two-dimensional or three-dimensional cases.
There are introduced novel variants of defining the discrete logarithm problem in a hidden group, which represents interest for constructing post-quantum cryptographic protocols and algorithms. This problem is formulated over finite associative algebras with non-commutative multiplication operation. In the known variant this problem, called congruent logarithm, is formulated as superposition of exponentiation operation and automorphic mapping of the algebra that is a finite non-commutative ring. Earlier it has been shown that congruent logarithm problem defined in the finite quaternion algebra can be reduced to discrete logarithm in the finite field that is an extension of the field over which the quaternion algebra is defined. Therefore further investigations of the congruent logarithm problem as primitive of the post-quantum cryptoschemes should be carried out in direction of finding new its carriers. The present paper introduces novel associative algebras possessing significantly different properties than quaternion algebra, in particular they contain no global unit. This difference had demanded a new definition of the discrete logarithm problem in a hidden group, which is different from the congruent logarithm. There are proposed several variants of such definition, in which it is used the notion of the local unite. There are considered right, left, and bi-side local unites. Two general methods for constructing the finite associative algebras with non-commutative multiplication operation are proposed. The first method relates to defining the algebras having dimension value equal to a natural number m > 1, and the second one relates to defining the algebras having arbitrary even dimensions. For the first time the digital signature algorithms based on computational difficulty of the discrete logarithm problem in a hidden group have been proposed.
The problem of walking robots controlled motion synthesis by the inverse dynamic method is considered. The inverse dynamic method equations are represented by the methods of multibody system dynamics as free bodies motion equations and constraint equations. The variety of constraint equations group are introduced to specify the robot gait, to implement the robot stability conditions and to coordinate specified robot links movement. The key feature of the inverse dynamic method equations in this formulation is the presence of the second derivatives of the system coordinates in the constraint equations expressing the stability conditions that ensure the maintenance of the vertical position by the robot. The determined solution of such equations in general case is impossible due to the uncertainty of the initial conditions for the Lagrange multipliers. An approximate method for solving the inverse dynamic without taking into account the inertial components in the constraint equations that determine the stability of the robot is considered. Constraint equations that determine the coordinate movement of individual robot links and required for unique problem solving based on approximate equations are presented. The implementation of program motion synthesis methods in the control system of the humanoid robot AR-600 is presented. The comparison of theoretical and experimental parameters of controlled motion is performed. It has been established that with the achieved high accuracy of the robot links tracking drives control with an error of several percent, the indicators of the robot's absolute movements, in particular, the angles of roll, yaw and pitch, differ from the programmed by 30-40%. It’s shown that proposed method allows to synthesize robot control in quasistatic mode for different movement types such as moving forward, sideways, walking on stairs, inclinations etc.
The most important task of modern robotics is the development of robots to perform the work in potentially dangerous fields which can cause the risk to human health. Currently robotic systems can not become a full replacement for man for solving complex problems in a dynamic environment despite an active development of artificial intelligence technologies.
The robots that implement the copying type of control or the so-called virtual presence of the operator are the most advanced for use in the nearest future. The principle of copying control is based on the motion capture of the remote operator and the formation of control signals for the robot’s drives. A tracking system or systems based on movement planning can be used to control the drives. The tracking systems are simpler, but systems based on motion planning allow to achieve more smooth motion and less wear on the parts of the control object. An artificial delay between the movements of the operator and the control object for necessary data collection is used to implement the control-based motion planning.
The aim of research is a reduction of delay, which appears when controlling the anthropomorphic manipulator drives based on the solution of the inverse dynamic problem, when real time copying type of control is used . For motion path planning it is proposed to use forecast values of the generalized coordinates for manipulator. Based on the measured values of the generalized coordinates of the operator's hand, time series are formed and their prediction is performed. Predictive values of generalized coordinates are used in planning the anthropomorphic manipulator trajectory and solving the inverse dynamic problem. Prediction is based on linear regression with relatively low computational complexity, which is an important criterion for the system operation in the real time operation mode. The developed mathematical apparatus, based on prediction parameters and maximum permissible accelerations of the manipulator drives, allows to find a theoretical estimate of error values limits for planning the operator's hand trajectory using the proposed approach for specific tasks. The adequacy of the maximum theoretical value of the prediction error, as well as the prospects of the proposed approach for testing in practice is confirmed by the software simulation in Matlab environment.
The short historical sketch of researches of efficiency of systems functioning purposeful processes is given in this paper. The review of some relevant research problems of the operational properties solved abroad is provided.
On the basis of the analysis of features of efficiency research of systems functioning purposeful processes, as well as research of other operational properties, such as effectiveness, performance, operational and dynamic capabilities by domestic and foreign authors, the conclusion is drawn on relevance of the solution of some modern research problems on the basis of analytical estimation of operational properties indicators. A number of new systems and processes of their functioning operational properties researches directions is given. Among them, there are system capability (potentiality) and information technologies capability. Features of agile (dynamical, improved due to environment impact) systems and processes of their functioning, a role of information technologies are considered during functioning of such agile systems.
Main features of systems improvement and details of transition processes of such systems functioning improvement are described. The role of information technologies for systems improvement is discussed. The obtained results allowed to conduct research of operational properties of the improved systems, research of information technologies usage during system functioning. Examples of models of the improved system functioning effects formation are offered. Such models are developed taking into account the realization of information and non-information actions during the improved system functioning.
For the unified estimation of indicators of operational properties the method of analytical estimation of operational properties is offered. This method is based on the sequence of operational properties estimation schemes use. The sequence of the three schemes of operational properties estimation, which allows to estimate all described operational properties. Features of estimation of systems operational properties using the offered estimation method are revealed. The obtained results should allow to proceed to the solution of research problems of systems operational properties based on mathematical models use. An example of operational properties of information technology use indicators calculation is provided.
The paper deals with the processing of hydroacoustic data recorded with help of hydroacoustic research complexes. Particular attention to classic and interferometric sonars is paid. In accordance to the regulatory documentation, the minimum permissible measurement errors for the formation of bottom surface maps for various economic sectors are determined.
As one of the important problems affecting the effectiveness of survey work with sonar complexes, the authors determine the problem of primary data compression, which, as a rule, leads to information loss without the possibility of its recovery. These drawbacks of the methods of primary information compression-recovery and processing of hydroacoustic data used in complexes reduce the overall effectiveness of the complexes usage both with the use of sidescan sonar and with the use of an interferometric side-scan sonar.
In the framework of a numerical experiment, it has been shown that the use of chirp signals as probing pulses makes it possible to effectively apply the complex in the survey sonar mode.
The results of the numerical experiment for estimating the spatial position of the object at the bottom of the sonar images using the phase difference information of the received signals using an interferometric sonar are presented. Based on the results of the experiment, the requirements for recording quality of reflected signals of various types in interferometric side-scan sonar are determined.
A method of resolving the reflected (with partial overlap and overlay) hydroacoustic tones, based on the method of dividing the spectra is proposed by the authors. To improve the efficiency of the chirp signal processing, the authors suggest to improve the accuracy of the detection of the signal detection time due to the phase correction calculated through the slope of the frequency change rate of the chirp signal.
An algorithm for the formation of a set of effective classification features, based on the truncated search concept and the use of the information about individual classification indicators in the granules selection, is proposed. Its computational efficiency is ensured by the use of simple comparison operations of classification results of individual classes when choosing the most informative granule at the next iteration and using the parallel computing technology on graphics processing units.
Known methods of the truncated selection for the formation of sets of effective classification features are considered. The results of the informative features search are discussed through the example of solving the cloud classification problem on the basis of the application of a probabilistic neural network and the texture information of MODIS satellite imagery. A description of the used classifier and the statistical approach to describing the texture of images is given.
The most effective cloud classification characteristics are determined by comparing the combinations of textural features obtained by truncated selection methods. The study results of the change dynamics in the correctly classified clouds estimation when performing various algorithms for informative features searching are shown. It is established that the method, developed in this paper, makes it possible to reduce the variance of probability values of the correct classification of individual classes.
To reduce the complexity of the task of structural synthesis, it is divided into stages, during each of which the researcher, conducts (with the help of decision support systems) the synthesis and analysis of model systems for the given input requirements and restrictions. Structural optimization, in this context, is reduced to finding the extremum of a certain objective function, whose value is controlled by specified design parameters depending on the type of task.
To demonstrate how the simulation model works, the functional synthesis of the structure of information enterprise management system is considered, where the functional elements are the automated business processes, and the structural elements — automation facilities. A test case is made, where typical processes of budgeting, marketing, purchasing and sales, production and human resources are described as the functional elements.
The use of the developed model of functional synthesis is exemplified by the task of choosing software for the design of corporate information systems. On the basis of a series of experiments we have determined the set of possible solutions with the greatest value of the fitness function. It is established that the function value is affected by the number of redundant functions that contain selected structural elements.
Development of the data-communication equipment with high demands imposed is necessary for solving the problems of unmanned robots group control at various levels. In this paper, methods and algorithms for noise-immunity communication channel implementation are described. It is substantiated that communication equipments for these channels have to be special-purpose and have to use effective signal-code constructions that can adapt to changing environments. Features and options for multiple unmanned ground vehicles (UGV) control communications are described, the advantages and disadvantages of time division multiple access and frequency division multiple access are considered.
A preface and introduction article presents an article by Platon Sergeevich Poreckij which is a record of his lecture delivered on October 25, 1886. The preface contains short historical reference about P. S. Poreckij’s works in the field of mathematical logic and its application to other science, including the probability theory. The introduction article has the main goal to show how the beginning of logic-and-probabilistic method (LPM) was created at the end of the XIX century. LPM essence was in valid transition from logic equation between the events to algebraic equality between their probabilities. The article shows that LPM further development is connected to the necessity of evaluation of digital circuits reliability as well as structurally complex systems reliability and safety in 1960s. Scientific disputes and the possibility of combining mathematical logic and the probability theory do not stop in the XIX century. There are regular seminars and conferences held on this subject. We discuss the complex mathematical and philosophical question about the nature of fundamentally different concepts - the probabilistic logic (PL) and the logic of probability (LP).
In the article, we consider an approach to justification of communication network modernization on introduction of new communication services. Optimality criterion of network completions is economic efficiency. Problems of introduction of new communication services are analyzed. The structurally functional model of communication network modernization and a model of decision-making at the choice of optimum by the set criterion of completions of each communication network system are given. Results of modeling are illustrated by a settlement example.
Lecture of P.S. Poreckii hold on October, 25th 1886, at the 60th Meeting of Section for Physic and Mathematics of the Scientific Society of the Imperial Kazan University. It is published in the original edition of 1886 (Poretsky P.S. Solution of the general problems of probability theory with the help of mathematical logic. - The meeting protocols of the 60th meeting of the Section of Physics and Mathematics Society of Naturalists at Kazan University, Kazan, 1886, pp 1-34).
The development of factorization mechanisms of composite integer numbers is examined in this work. The author proposes a different approach, based on the study of the internal structure of the positive integers and the use of the properties of numbers which do not depend on their digits (the criterion for divisibility). That kind of approach provides a conversion from integer factorization task to a retrieval task of the special partition of the new characteristic of a number , so-called f-invariant, which turns out to be less complex problem. – Bibl. 22 items.
The development of factorization mechanisms of composite integer numbers is considered in this work. The existent methods will not become more rapid and efficient in the nearest decade, due to narrow and inadequate mathematical approach to solution of this problem, which is based on so-called sieve of Eratosthenes. The mechanism suggested by author of this work, uses a completely new method based on examination of internal structure of natural sequence and application of digit place independent features (the criterion for divisibility).
The paper describes the original algorithm of a heterogeneous data clustering is based on complex application of a set of measures of distances and clustering methods and multi-stage clustering. In the algorithm we use ranging of attributes the object on their importance for group and a choice of an optimum attributes set, ensemble approach to get the final clustering solution. The algorithm is realized in MixDC (Mixed Data Clustering) software system. The technique and results of the solution of a real problem of a medical data clustering in software system are described.
In article, on the example of the tasks arising at research of products properties, created at the enterprises of a military-industrial complex, problems of operational and ex-change properties of complex technical systems research are investigated. Operational properties of systems characterize results (effects) of activity with use of systems (op-erational properties, in particular, are efficiency of system functioning for achievement of the given objective, system potential, system capabilities). Exchange properties characterize properties of exchange of results of activity (exchange properties, in par-ticular, are competitiveness of a product, competitiveness of the enterprise). As shown, it is expedient to study exchange properties of systems using the concept and method-ology of estimation of operational properties of systems. Indicators for operational properties estimation proposed and on their basis indicators for exchange properties of the systems suggested. Indicators suggested in such a way that their estimation suppose usage of mathematical models. This gives the chance to solve a range of research prob-lems of operational and exchange properties of systems. Need of definition of concept is proved, and then the concept of model of a research problem proposed. The direc-tions of research problems models usage for automation of the solution of operational and exchange properties research problems discussed.
A problem of construction of a level description of classes with objects characterized by properties of their elements and relations between them is under consi\-de\-ration in the paper. The problems of recognition and analysis of such objects are NP-hard, but if descriptions of classes contain short enough and frequently occurred sub-formulas then it is possible to build a level description of classes essentially decreasing an exponent in upper bounds of steps for an algorithm solving the problemr. Usually an extracting of these sub-formulas is leaved to the investigator will. An approach to their automatic extraction is proposed in the paper.
The plan operation correction problem of ground based space monitoring information system is considered in this paper. The generalized algorithm of the positional control construction is proposed and illustrated on the numerical example.
User behaviour models represent important features used to enhance web search results; they are usually probabilistic models learned from logs of user actions (click logs). We present a survey of modern user behaviour models and review how behaviour models are combined with other features in the ranking function.
The paper encompasses design and analysis of combined protection mechanisms applied to complex communication systems containing embedded and mobile devices. A notion of configuration is proposed in order to represent a combination of particular security building blocks deployed to support security of the device as well as software services it provides. Starting from functional and non-functional properties of specific building blocks the optimization problem allows arranging the search of the most effective configuration. Effectiveness evaluation of the configuring approach is conducted by means of its comparing with alternative configuring strategies, including ―manual‖ configuring scenarios realized by an operator of the system without using any automated tools for enumeration and evaluation of configurations.
Some artificial intelligence problems including such ones as pattern recognition, medical diagnostics, market analysis is reduced to the proof of satisfi\-abi\-li\-ty of predicate calculus formulas with a symple structure. Some algorithms solving such problems are regarded and the upper bounds of their steps are proved.
The class of problems in socio-economic systems is considered, such that problems decision demands capability estimation. Challenge of systems capability estimation formulated. It is shown that analytical estimation of capability on the base of systemic concepts application is necessary. System capability property is defined, capability problems solving topicality justified. Concept of capability research problems solving suggested, capability indicators are justified. Few socio-economic systems capability research problem statements are considered.
The application of the fractal dynamic analysis method to tensometrical data is results in some variables appearance. There is a problem of features extraction in the paper. Features calculation methods, classification methods and features extraction criteria are discussed. The review of features extraction algorithms are represented.
The problems of creating and using of fault-tolerant computer systems is considered. The article presents different solutions of problem of structure dynamic control for the fault-tolerant computer systems functioning in high availability and load balancing modes.
Algorithms of priorities assignment for real-time systems inclusive simple and complex tasks are discussed. The algorithms provide RAM use efficiency increase.
An ideal of conjunctions with a probabilistic estimates/assignment of its elements is one of the mathematical models of a knowledge pattern with probabilistic uncertainty. Chains and networks of such ideals are mathematical models of knowledge pattern bases; these models are referred to as algebraic Bayesian networks. We consider extremal tasks that appear in conjunction chains ideals when elementary evidence or a set of such evidence is propagated over them. This propagation is referred to as à posteriori inference. We also generalize our approach to evidence propagation onto chains of conjunctions ideals and acyclic networks of those ideals. Initially appearing extremal tasks are hyperbolic programming ones; but we manage to reduce them to linear programming tasks. We describe as well an indexation of ideal elements. This indexation allows to formally specify a set of constraints, originated from probabilistic logic axioms, over a conjunctions ideal. This formal specification allows a convenient notation of the extremal tasks under question.
The Deep Data Diver system uses a new technology of associative rules search which is based on modified tools of linear algebra and the usage of a data self-organization procedure and an informational structural resonance effect. The unique characteristics of the system allow to search data for highly accurate associations of the items comprising the initial transaction set with a given item. These sets form a basket with high support level and long itemsets. The article provides a general overview of the Deep Data Diver system and gives the comparison results of solving the specific task of market basket analysis.
In the paper, a knowledge pattern with probabilistic uncertainty is considered. The process of consistency maintenance for this knowledge pattern is described. The code using object-oriented ILOG Planner’s C++ library implementing the representation of knowledge patterns and the process of consistency maintenance is given.
Introduction : Modern complex technical systems are often critical. Criticality is due to the consequences of disruption of the functioning of such systems, and their failure to fulfill the required list of functions and tasks. The process of control and management of such systems is carried out using communication systems and networks that become critical for them. There is a need to ensure the stable functioning of the complex technical systems themselves, their control and monitoring systems, communication systems and networks. The paper proposes a method for ensuring the functional stability of a communication system, the basis of which is the process of identifying and eliminating conflicts in it due to the difference between the profile of functioning and the profile of the process of functioning of the system. The proposed model of the process of functioning of the communication system allows, based on changes in the intensity of the impact on the system of destabilizing factors, the identification of conflicts and their elimination, to determine the probability of ensuring the functional stability of the system. The purpose of the study: to develop a methodology for ensuring the functional stability of a communication system under the influence of destabilizing factors and the emergence of conflicts, a model of the process of the system's functioning, which makes it possible to determine the probability of the system being in a functionally stable state. Methods of graph theory and matrix theory, the theory of Markov processes. Results: an approach is proposed for assessing the functional stability of a communication system under the influence of destabilizing factors, a technique has been developed to ensure the functional stability of a communication system. Practical significance: the results of the study can be used in the design and construction of complex technical systems, decision support systems, control, communication and management.
The paper presents the results of statistical data from open sources on the development of the COVID-19 epidemic processing and a study сarried out to determine the place and time of its beginning in Russia. An overview of the existing models of the processes of the epidemic development and methods for solving direct and inverse problems of its analysis is given. A model for the development of the COVID-19 epidemic via a transport network of nine Russian cities is proposed: Moscow, St. Petersburg, Nizhny Novgorod, Rostov-on-Don, Krasnodar, Yekaterinburg, Novosibirsk, Khabarovsk and Vladivostok. The cities are selected both by geographic location and by the number of population. The model consists of twenty seven differential equations. An algorithm for reverse analysis of the epidemic model has been developed. The initial data for solving the problem were the data on the population, the intensity of process transitions from one state to another, as well as data on the infection rate of the population at given time moments. The paper also provides the results of a detailed analysis of the solution approaches to modeling the development of epidemics by type of model (basic SEIR model, SIRD model, adaptive behavioral model, modified SEIR models), and by country (in Poland, France, Spain, Greece and others) and an overview of the applications that can be solved using epidemic spread modeling. Additional environmental parameters that affect the modeling of the spread of epidemics and can be taken into account to improve the accuracy of the results are considered. Based on the results of the modeling, the most likely source cities of the epidemic beginning in Russia, as well as the moment of its beginning, have been identified. The reliability of the estimates obtained is largely determined by the reliability of the statistics used on the development of COVID-19 and the available data on transportation network, which are in the public domain.
One of the main problems facing the developer of a system with a neural network is the choice of the structure of a neural network that could solve the tasks. At present there are no unambiguous recommendations for choosing such a structure and such parameters as: the number of layers, the number of neurons in the layer, the type of neuron nonlinearity, the training method, the parameters of the training method, and others.
The article considers an approach to the synthesis of a neural network for a class of logical-arithmetic problems, based on the formation of a network of pre-constructed elementary functions. The novelty of the proposed approach is the formation of a neural network using a well-known algorithm using pre-built functions. Thus, in the article elementary logical-arithmetic functions such as "and", "or", "exclusive or", "and-not", "or-not", "", "", ">", "<" are built, which can be used to solve more complex problems. An example of a solution to the problem of constructing a function for selecting the maximum number of four numbers represented in binary form in three digits is given. Synthesis of a neural network in the manner described above is performed with the further goal of obtaining a generalized structure of the neural network.
An improvement of existing navigation algorithms for a generic polygonal linkage is presented. Our algorithm constructs a path between two arbitrary configurations of a polygonal linkage. This path contains att most eight steps
The paper discusses features of construction and operation of automated systems of railway transport. As main distinguishing factors, the great variety and diversity of such systems, their mutual co-relationships and links with public networks, and strong heterogeneity of internal user are highlighted. The architecture of a multi-level intelligent information security system that proposed to protect information in automated systems of railway transport is suggested and discussed. To store data about security in a multilevel intelligent system of protection it is proposed to use a hybrid ontology repository. Formal task statements for intelligent services of data analysis at the top level of the reviewed protection systems are offered. Analysis of these statements showed that development of intelligent services for correlation management, security analysis and attack modeling should be assigned to analysis tasks. Intelligent services for decision support and visual data analysis are among the synthesis tasks.
In this article we treat a question how to develop a procedure of functional and parametric analysis, which is based on calculation of effectiveness of multifuncional complex operation during decision making; we offer correlations for calculation, mark practicability of adding of support devices to information complexes.
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