A method of constructing a transport network using a satellite image and a set of paths as input data is considered. Software has been developed for building a transport network model based on the specified input data. Examples of the program's operation on various sections of transport networks are considered. The advantages and disadvantages of the developed method are described.
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This survey focuses on the following problem: it is necessary, observing the behaviour of the object, automatically figure out how to improve (optimize) the quality of his functioning and to identify constraints to the improvement of this quality. In other words, build the objective function (or set of objective functions in multiobjective case) and constraints - i.e. the mathematical model of optimization - by mean machine learning.
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In this paper, some properties of basis invariants of the unitary group $W (J_3(4))$ of order 336 generated by reflections in 3-dimensional unitary space are studied. There is developed a new method of finding in explicit form the basic invariants of group $W(J_3(4))$. This method is based on the following property of group $W(J_3(4))$ – group $W(J_3(4))$ contains group $B_3$ of symmetries of the cube, and Pogorelov polynomials of the form $$
J_{m_i}(G) = \sum\limits_{\sigma \in G}(\overrightarrow{x}, \sigma\ \overrightarrow{s})^{m_i},
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The problem of optimal strategy founding of the repair organization for the system that is described bi the semi-Markov process is investigated. The statements about the optimal strategy existence are proved, the optimal strategy structure is found.
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The sufficient condition for existence of linear function's ∑ N+1K=0(lk ∣ xk)Rn minimax estimations is obtained on the basis of observations yk = Hkxk + η k up to N moment assuming that lk &n; Rn, xk is a solution of the linear descriptor difference equation Fk+1xk+1 − Ckxk = fk, F0x0 = g0, k = 0, N, g0, fk - are some unknown vectors from the set G, η k - is random vector with unknown correlation matrix Rk which belongs to set G2.
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A general approach to transmission problems was considered in the author’s previous work ([14], [15]). It consists in the fact that the solution of an inhomogeneous problem is sought in the form of a sum of solutions of auxiliary homogeneous problems. In these auxiliary problems, the inhomogeneity is contained only in one place, that is, either in the equation or in the boundary condition. The solution of each of the auxiliary problems is found by means of the corresponding Green’s formulas ([10], [14]).
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The classification and constructive description of matrices consisting of the linear forms and having a rank ≤ 3 are obtained.
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The present work is devoted to one of the tasks of modern scientific research related to the construction and verification of models that allow to organize and systematize a significant amount of information (Big Data) of real systems for making decisions on development and optimization.
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The new method for ensemble learning is proposed - Cooperative Coevolution Ensemble Learner (CCEL), based on special genetic algorithm. It can be used as a wrapper over any kind of weak algorithms, learning procedures and fusion functions. Experiments on 12 real-world problems from UCI repository show that CCEL has a fairly high generalization performance and constructs ensembles of much smaller size than boosting, bagging and random subspaces method.
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In the paper, we consider the problem on small motions of three viscoelastic fluids in a stationary container. One of models of such fluids is Oldroid’s model. It is described, for example, in the [1]. It should be noted that the present paper based on the previous N. D. Kopachevsky and his co-authors works [2, 3, 4]. Namely, problem on small movements of two viscoelastic fluids has already investigated in [2].
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This paper is devoted to study constructive possibilities for application of irreducible representations of complex algebras to the description of finite dimensional irreducible representations of real algebras on quaternionic modules.
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The problems of development of Information Control Systems with the factor of high data quantity growth are discussed. Hierarchical structure of the system goals is proposed. It is shown the role of unification and formalization of documents, which circulate in the System.
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In this work conditions of existing of orthogonal algebraic bases in lineals and complete orthogonal systems in (closed with respect to certain topology) subspaces of indefinite inner product spaces are investigated.
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Let $H$ be a Hilbert space and let $A: \mathscr{D}(A) \subset H \to H$ be a selfadjoint positive definite operator, $A^{-1} \in \mathscr{G}^q(H)\ (q>0),\ \beta_l \gt 0\ (l = \overline{0, m}), \ 0 = : b_0 \lt b_1 \lt \cdots \lt b_m$.
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In this article the notion of the template of set functions and various kinds of such templates are introduced. Are considered primary k-parametrical templates of a kind t = t[+, •].The Vapnick Chevronenkis Dimension (VCD) for image of such templates is estimated. As well as VCD for the class of polynomials above a field of real (rational) numbers and the class of Zhegalkin polynomials are estimated.
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The solvability of the smooth transition equation in the Hilbert space double-index scale well adjusted for Fourier transform and convolution type equation solving in considered.
Compact component and abbreviated interval structures of attribute space generated by empirical data
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The compact component structure of attributes space, clustering algorithm based on this concept, the brief interval structure concept of attributes space and its construction algorithm are considered in the paper.
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This paper is devoted to the description of all irreducible representations of some real involutive algebras on Hilbert quaternionic bimodules, naturally arising is resulting at consideration of nonequivalent involutions of graduated analogue of Lee algebra о(2,H).
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The problem of multicriteria Pseudo-Boolean optimization for the case of partially given objective function is considered. The analysis of algorithms (branches and borders method, criterion linear fold, locals search) for solving bicriteria problems of Pseudo-Boolean linear optimization is carried out when criteria are represented by the information on the coefficient signs.
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The problem of finding the most appropriate subset of features or regressors is the generic challenge of Machine Learning problems like regression estimation or pattern recognition. We consider the problem of time-varying regression estimation, which implies also the inevitable necessity to choose the individual appropriate levels of model volatility in each of regressors, ranging from the full stationarity of instant models to their absolute inde-pendence in time.
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Problems arising up at the decision of tasks of operative regional and department management are considered in the work. Management methods are offered for thousands of remote organizations on the basis of heterogeneous information.
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Theoretical preconditions and program realization of computer system of indexing and abstracting of text documents on the basis of knowledge base use about a subject domain in the form of an is situational-syntagmatic network are considered. The approach offered by authors to calculation informative lexemes and the offers, based on comparison of statistical characteristics of word forms in the reviewed text and a full corpus is used in this system.
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In this article the grayscale image skeletonization problem is shown by the example of images of fingertips prints. The main idea: the grayscale image skeleton is constructed using some parts of binary images skeletons. One can take these binary images after initial grayscale picture binarization with various brightness levels. Such binary images skeletons fragments give us the opportunity constructing clear binary image of initial grayscale picture.
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A lot of image analysis problems lend themselves to a unified mathematical formulation as optimization problems, namely (min, +)labelling problems. It is known that these problems are NP-hard in the general formulation, but when the adjacency graph is a tree, they can be effectively solved by the tree-serial dynamic programming procedure. In this paper, it is considered an optimization method on the basis of Gauss-Seidel principle, which uses iterative reevaluation of groups of variables with tree-like neighborhood relation.
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We consider systems described by initial-boundary value problems for parabolic equations with discontinuous coefficients. From observations of the state of systems, we find minimax prediction estimates
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This paper is dedicated to the problem of image retrieval from large databases of biomedical images using the query by example paradigm. The specific characteristics of biomedical images are briefly discussed in the context of similarity retrieval and possible ways of image searching are outlined. A versatile method is suggested which is based on extended multi-sort and multi-dimensional co-occurrence matrices. The use of the method is illustrated on a variety of image retrieval tasks using real databases of biomedical images of different types.
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The paper considers multidimensional scaling problem with proximity matrix consisting of two different non-diagonal elements. Elements of the superdiagonal matrix don’t decrease along the string and don’t increase along the column. The structure of considered matrix is described. In one-, two- and three-dimensional spaces all available proximity matrices are listed. Matrices that can be considered as proximity matrices in t-dimensional euclidian space have their dimensions in a definite interval. The exact bounds of this interval are also found.
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The notion of the key antichain for the lattice of characteristic space interval descriptions, key antichains family property, the algorithm of the key antichains construction are conside the paper.
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An algorithm for calculating dense disparity map for stereo images is proposed. Stereo correspondence problem is formulated in terms of an assignment problem in this algorithm. The algorithm processes each image scan-line individually similar to a dynamic programming approach to the dense stereo correspondence problem, however unlike dynamic programming, it does not rely on ordering constraint. Ordering constraint elimination is useful for the scenes with narrow objects in front of the camera. The proposed algorithm supports occlusions detection and guaranties uniquness of found matches.
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The results received last years within the limits of the algebraic approach to the recognition problems are described. Algebraic closures of algorithms of classical estimation algorithm model are investigated.