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Найдено статей: 666
  1. Gasnikov A.V., Gorbunov E.A., Kovalev D.A., Mohammed A.A., Chernousova E.O.
    The global rate of convergence for optimal tensor methods in smooth convex optimization
    Computer Research and Modeling, 2018, v. 10, no. 6, pp. 737-753

    In this work we consider Monteiro – Svaiter accelerated hybrid proximal extragradient (A-HPE) framework and accelerated Newton proximal extragradient (A-NPE) framework. The last framework contains an optimal method for rather smooth convex optimization problems with second-order oracle. We generalize A-NPE framework for higher order derivative oracle (schemes). We replace Newton’s type step in A-NPE that was used for auxiliary problem by Newton’s regularized (tensor) type step (Yu. Nesterov, 2018). Moreover we generalize large step A-HPE/A-NPE framework by replacing Monteiro – Svaiter’s large step condition so that this framework could work for high-order schemes. The main contribution of the paper is as follows: we propose optimal highorder methods for convex optimization problems. As far as we know for that moment there exist only zero, first and second order optimal methods that work according to the lower bounds. For higher order schemes there exists a gap between the lower bounds (Arjevani, Shamir, Shiff, 2017) and existing high-order (tensor) methods (Nesterov – Polyak, 2006; Yu.Nesterov, 2008; M. Baes, 2009; Yu.Nesterov, 2018). Asymptotically the ratio of the rates of convergences for the best existing methods and lower bounds is about 1.5. In this work we eliminate this gap and show that lower bounds are tight. We also consider rather smooth strongly convex optimization problems and show how to generalize the proposed methods to this case. The basic idea is to use restart technique until iteration sequence reach the region of quadratic convergence of Newton method and then use Newton method. One can show that the considered method converges with optimal rates up to a logarithmic factor. Note, that proposed in this work technique can be generalized in the case when we can’t solve auxiliary problem exactly, moreover we can’t even calculate the derivatives of the functional exactly. Moreover, the proposed technique can be generalized to the composite optimization problems and in particular to the constraint convex optimization problems. We also formulate a list of open questions that arise around the main result of this paper (optimal universal method of high order e.t.c.).

    Views (last year): 75.
  2. Kondratyev M.A.
    Forecasting methods and models of disease spread
    Computer Research and Modeling, 2013, v. 5, no. 5, pp. 863-882

    The number of papers addressing the forecasting of the infectious disease morbidity is rapidly growing due to accumulation of available statistical data. This article surveys the major approaches for the shortterm and the long-term morbidity forecasting. Their limitations and the practical application possibilities are pointed out. The paper presents the conventional time series analysis methods — regression and autoregressive models; machine learning-based approaches — Bayesian networks and artificial neural networks; case-based reasoning; filtration-based techniques. The most known mathematical models of infectious diseases are mentioned: classical equation-based models (deterministic and stochastic), modern simulation models (network and agent-based).

    Views (last year): 71. Citations: 19 (RSCI).
  3. Lobanov A.I.
    Model of cellular automata
    Computer Research and Modeling, 2010, v. 2, no. 3, pp. 273-293

    An introduction to the models of cellular automata is given. The three automata described on the plane are: Viner-Rosenbluth cellular automata, the game of Life and Kohomoto-Oono automata for modelling «reaction-diffusion» systems. There is built the generalization of cellular automata of the game of Life to arbitrary dimension of space and the generalization of Kohomoto-Oono automata in 3D.

    Views (last year): 64. Citations: 21 (RSCI).
  4. Simakov S.S.
    Modern methods of mathematical modeling of blood flow using reduced order methods
    Computer Research and Modeling, 2018, v. 10, no. 5, pp. 581-604

    The study of the physiological and pathophysiological processes in the cardiovascular system is one of the important contemporary issues, which is addressed in many works. In this work, several approaches to the mathematical modelling of the blood flow are considered. They are based on the spatial order reduction and/or use a steady-state approach. Attention is paid to the discussion of the assumptions and suggestions, which are limiting the scope of such models. Some typical mathematical formulations are considered together with the brief review of their numerical implementation. In the first part, we discuss the models, which are based on the full spatial order reduction and/or use a steady-state approach. One of the most popular approaches exploits the analogy between the flow of the viscous fluid in the elastic tubes and the current in the electrical circuit. Such models can be used as an individual tool. They also used for the formulation of the boundary conditions in the models using one dimensional (1D) and three dimensional (3D) spatial coordinates. The use of the dynamical compartment models allows describing haemodynamics over an extended period (by order of tens of cardiac cycles and more). Then, the steady-state models are considered. They may use either total spatial reduction or two dimensional (2D) spatial coordinates. This approach is used for simulation the blood flow in the region of microcirculation. In the second part, we discuss the models, which are based on the spatial order reduction to the 1D coordinate. The models of this type require relatively small computational power relative to the 3D models. Within the scope of this approach, it is also possible to include all large vessels of the organism. The 1D models allow simulation of the haemodynamic parameters in every vessel, which is included in the model network. The structure and the parameters of such a network can be set according to the literature data. It also exists methods of medical data segmentation. The 1D models may be derived from the 3D Navier – Stokes equations either by asymptotic analysis or by integrating them over a volume. The major assumptions are symmetric flow and constant shape of the velocity profile over a cross-section. These assumptions are somewhat restrictive and arguable. Some of the current works paying attention to the 1D model’s validation, to the comparing different 1D models and the comparing 1D models with clinical data. The obtained results reveal acceptable accuracy. It allows concluding, that the 1D approach can be used in medical applications. 1D models allow describing several dynamical processes, such as pulse wave propagation, Korotkov’s tones. Some physiological conditions may be included in the 1D models: gravity force, muscles contraction force, regulation and autoregulation.

    Views (last year): 62. Citations: 2 (RSCI).
  5. Matyushkin I.V., Zapletina M.A.
    Cellular automata review based on modern domestic publications
    Computer Research and Modeling, 2019, v. 11, no. 1, pp. 9-57

    The paper contains the analysis of the domestic publications issued in 2013–2017 years and devoted to cellular automata. The most of them concern on mathematical modeling. Scientometric schedules for 1990–2017 years have proved relevance of subject. The review allows to allocate the main personalities and the scientific directions/schools in modern Russian science, to reveal their originality or secondness in comparison with world science. Due to the authors choice of national publications basis instead of world, the paper claims the completeness and the fact is that about 200 items from the checked 526 references have an importance for science.

    In the Annex to the review provides preliminary information about CA — the Game of Life, a theorem about gardens of Eden, elementary CAs (together with the diagram of de Brujin), block Margolus’s CAs, alternating CAs. Attention is paid to three important for modeling semantic traditions of von Neumann, Zuse and Zetlin, as well as to the relationship with the concepts of neural networks and Petri nets. It is allocated conditional 10 works, which should be familiar to any specialist in CA. Some important works of the 1990s and later are listed in the Introduction.

    Then the crowd of publications is divided into categories: the modification of the CA and other network models (29 %), Mathematical properties of the CA and the connection with mathematics (5 %), Hardware implementation (3 %), Software implementation (5 %), Data Processing, recognition and Cryptography (8 %), Mechanics, physics and chemistry (20 %), Biology, ecology and medicine (15 %), Economics, urban studies and sociology (15 %). In parentheses the share of subjects in the array are indicated. There is an increase in publications on CA in the humanitarian sphere, as well as the emergence of hybrid approaches, leading away from the classic CA definition.

    Views (last year): 58.
  6. Dushkin R.V.
    Review of Modern State of Quantum Technologies
    Computer Research and Modeling, 2018, v. 10, no. 2, pp. 165-179

    At present modern quantum technologies can get a new twist of development, which will certainly give an opportunity to obtain solutions for numerous problems that previously could not be solved in the framework of “traditional” paradigms and computational models. All mankind stands at the threshold of the so-called “second quantum revolution”, and its short-term and long-term consequences will affect virtually all spheres of life of a global society. Such directions and branches of science and technology as materials science, nanotechnology, pharmacology and biochemistry in general, modeling of chaotic dynamic processes (nuclear explosions, turbulent flows, weather and long-term climatic phenomena), etc. will be directly developed, as well as the solution of any problems, which reduce to the multiplication of matrices of large dimensions (in particular, the modeling of quantum systems). However, along with extraordinary opportunities, quantum technologies carry with them certain risks and threats, in particular, the scrapping of all information systems based on modern achievements in cryptography, which will entail almost complete destruction of secrecy, the global financial crisis due to the destruction of the banking sector and compromise of all communication channels. Even in spite of the fact that methods of so-called “post-quantum” cryptography are already being developed today, some risks still need to be realized, since not all long-term consequences can be calculated. At the same time, one should be prepared to all of the above, including by training specialists working in the field of quantum technologies and understanding all their aspects, new opportunities, risks and threats. In this connection, this article briefly describes the current state of quantum technologies, namely, quantum sensorics, information transfer using quantum protocols, a universal quantum computer (hardware), and quantum computations based on quantum algorithms (software). For all of the above, forecasts are given for the development of the impact on various areas of human civilization.

    Views (last year): 56.
  7. Yevin I.A.
    Introduction to the theory of complex networks
    Computer Research and Modeling, 2010, v. 2, no. 2, pp. 121-141

    There was a new direction of studying of the complex systems last years, considering them as networks. Nodes in such networks represent elements of these complex systems, and links between nodes – interactions between elements. These researches deal with real systems, such as biological (metabolic networks of cells, functional networks of a brain, ecological systems), technical (the Internet, WWW, networks of the companies of cellular communication, power grids), social (networks of scientific cooperation, a network of movie actors, a network of acquaintances). It has appeared that these networks have more complex architecture, than classical random networks. In the offered review the basic concepts theory of complex networks are given, and the basic directions of studying of real networks structures are also briefly described.

    Views (last year): 53. Citations: 107 (RSCI).
  8. Karpov V.E.
    Introduction to the parallelization of algorithms and programs
    Computer Research and Modeling, 2010, v. 2, no. 3, pp. 231-272

    Difference of software development for parallel computing technology from sequential programming is dicussed. Arguements for introduction of new phases into technology of software engineering are given. These phases are: decomposition of algorithms, assignment of jobs to performers, conducting and mapping of logical to physical performers. Issues of performance evaluation of algorithms are briefly discussed. Decomposition of algorithms and programs into parts that can be executed in parallel is dicussed.

    Views (last year): 53. Citations: 22 (RSCI).
  9. Matyushkin I.V., Zapletina M.A.
    Computer research of the holomorphic dynamics of exponential and linear-exponential maps
    Computer Research and Modeling, 2018, v. 10, no. 4, pp. 383-405

    The work belongs to the direction of experimental mathematics, which investigates the properties of mathematical objects by the computing facilities of a computer. The base is an exponential map, its topological properties (Cantor's bouquets) differ from properties of polynomial and rational complex-valued functions. The subject of the study are the character and features of the Fatou and Julia sets, as well as the equilibrium points and orbits of the zero of three iterated complex-valued mappings: $f:z \to (1+ \mu) \exp (iz)$, $g : z \to \big(1+ \mu |z - z^*|\big) \exp (iz)$, $h : z \to \big(1+ \mu (z - z^* )\big) \exp (iz)$, with $z,\mu \in \mathbb{C}$, $z^* : \exp (iz^*) = z^*$. For a quasilinear map g having no analyticity characteristic, two bifurcation transitions were discovered: the creation of a new equilibrium point (for which the critical value of the linear parameter was found and the bifurcation consists of “fork” type and “saddle”-node transition) and the transition to the radical transformation of the Fatou set. A nontrivial character of convergence to a fixed point is revealed, which is associated with the appearance of “valleys” on the graph of convergence rates. For two other maps, the monoperiodicity of regimes is significant, the phenomenon of “period doubling” is noted (in one case along the path $39\to 3$, in the other along the path $17\to 2$), and the coincidence of the period multiplicity and the number of sleeves of the Julia spiral in a neighborhood of a fixed point is found. A rich illustrative material, numerical results of experiments and summary tables reflecting the parametric dependence of maps are given. Some questions are formulated in the paper for further research using traditional mathematics methods.

    Views (last year): 51. Citations: 1 (RSCI).
  10. Krasnyakov I.V., Bratsun D.A., Pismen L.M.
    Mathematical modeling of carcinoma growth with a dynamic change in the phenotype of cells
    Computer Research and Modeling, 2018, v. 10, no. 6, pp. 879-902

    In this paper, we proposed a two-dimensional chemo-mechanical model of the growth of invasive carcinoma in epithelial tissue. Each cell is modeled by an elastic polygon, changing its shape and size under the influence of pressure forces acting from the tissue. The average size and shape of the cells have been calibrated on the basis of experimental data. The model allows to describe the dynamic deformations in epithelial tissue as a collective evolution of cells interacting through the exchange of mechanical and chemical signals. The general direction of tumor growth is controlled by a pre-established linear gradient of nutrient concentration. Growth and deformation of the tissue occurs due to the mechanisms of cell division and intercalation. We assume that carcinoma has a heterogeneous structure made up of cells of different phenotypes that perform various functions in the tumor. The main parameter that determines the phenotype of a cell is the degree of its adhesion to the adjacent cells. Three main phenotypes of cancer cells are distinguished: the epithelial (E) phenotype is represented by internal tumor cells, the mesenchymal (M) phenotype is represented by single cells and the intermediate phenotype is represented by the frontal tumor cells. We assume also that the phenotype of each cell under certain conditions can change dynamically due to epithelial-mesenchymal (EM) and inverse (ME) transitions. As for normal cells, we define the main E-phenotype, which is represented by ordinary cells with strong adhesion to each other. In addition, the normal cells that are adjacent to the tumor undergo a forced EM-transition and form an M-phenotype of healthy cells. Numerical simulations have shown that, depending on the values of the control parameters as well as a combination of possible phenotypes of healthy and cancer cells, the evolution of the tumor can result in a variety of cancer structures reflecting the self-organization of tumor cells of different phenotypes. We compare the structures obtained numerically with the morphological structures revealed in clinical studies of breast carcinoma: trabecular, solid, tubular, alveolar and discrete tumor structures with ameboid migration. The possible scenario of morphogenesis for each structure is discussed. We describe also the metastatic process during which a single cancer cell of ameboid phenotype moves due to intercalation in healthy epithelial tissue, then divides and undergoes a ME transition with the appearance of a secondary tumor.

    Views (last year): 46.
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