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    Wyświetlanie 1-4 z 4
    Tytuł:
    Cellular Automata and Many-Particle Systems Modeling Aggregation Behavior Among Populations
    Autorzy:
    Morale, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/929762.pdf
    Data publikacji:
    2000
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    równanie różniczkowe stochastyczne
    równanie różniczkowo-całkowe
    cellular automata
    individual-based models
    stochastic differential equations
    law of large numbers
    density dependence
    nonlinear integrodifferential equations
    Opis:
    A cellular automaton model is presented in order to describe mutual interactions among the individuals of a population due to social decisions.The scheme is used for getting qualitative results, comparable to field experiments carried out on a population of ants which present an aggregative behavior. We also present a second description of a biological spatially structured population of N individuals by a system of stochastic differential equations of Ito type. A 'law of large numbers' to a continuum dynamics described by an integro-differential equation is given.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2000, 10, 1; 157-173
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Nonlinear filtering for Markov systems with delayed observations
    Autorzy:
    Calzolari, A.
    Florchinger, P.
    Nappo, G.
    Powiązania:
    https://bibliotekanauki.pl/articles/907856.pdf
    Data publikacji:
    2009
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    filtracja nieliniowa
    proces dyfuzji
    procesy Markova
    stochastyczne równanie różniczkowe
    nonlinear filtering
    jump processes
    diffusion processes
    Markov processes
    stochastic delay differential equation
    Opis:
    This paper deals with nonlinear filtering problems with delays, i.e., we consider a system (X,Y ), which can be represented by means of a system [...], in the sense that [...], where a(t) is a delayed time transformation. We start with X being a Markov process, and then study Markovian systems, not necessarily diffusive, with correlated noises. The interest is focused on the existence of explicit representations of the corresponding filters as functionals depending on the observed trajectory. Various assumptions on the function a(t) are considered.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2009, 19, 1; 49-57
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Stochastic models of the slow/fast type of atrioventricular nodal reentrant tachycardia and tachycardia with conduction aberration
    Autorzy:
    Jackowska-Zduniak, Beata
    Powiązania:
    https://bibliotekanauki.pl/articles/2172115.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    mathematical model
    stochastic differential equations
    action potential
    atrioventricular nodal reentrant tachycardia
    conduction aberration
    model matematyczny
    stochastyczne równanie różniczkowe
    potencjał czynnościowy
    częstoskurcz komorowy
    aberracja przewodzenia
    Opis:
    Models are proposed to describe the heart’s action potential. A system of stochastic differential equations is used to recreate pathological behaviour in the heart such as atrioventricular nodal reentrant tachycardia (AVNRT) and also AVNRT with conduction aberration. Part of the population has abnormal accessory pathways: fast and slow. An additional pathway is not always induced, since the deterministic model is not proper due to a stochasticity in this process. Introduction of a stochastic term allows modelling a pre-excitation perturbation (such as unexpected excitation by premature contractions in atrium (PAC)) which triggers the mechanism of AVNRT. Also, a system of AVNRT with additional conduction aberration, which is a rare type of arrhythmia, is considered. The aim of this work is to propose a mathematical model superior to the deterministic one that recreates this disease better and allows understanding its mechanism and physical dependencies, which may help to propose a new therapy of AVNRT. Results are illustrated with numerical solutions.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2022, 32, 3; 429--440
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A dynamic bi-orthogonal field equation approach to efficient Bayesian inversion
    Autorzy:
    Tagade, P. M.
    Choi, H. L.
    Powiązania:
    https://bibliotekanauki.pl/articles/330516.pdf
    Data publikacji:
    2017
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    Bayesian framework
    stochastic partial differential equation
    Karhunen–Loève expansion
    generalized polynomial chaos
    dynamically biorthogonal field equations
    ramy Bayesa
    stochastyczne równanie różniczkowe
    przekształcenie Karhunena-Loeve'a
    chaos wielomianowy
    Opis:
    This paper proposes a novel computationally efficient stochastic spectral projection based approach to Bayesian inversion of a computer simulator with high dimensional parametric and model structure uncertainty. The proposed method is based on the decomposition of the solution into its mean and a random field using a generic Karhunen–Loève expansion. The random field is represented as a convolution of separable Hilbert spaces in stochastic and spatial dimensions that are spectrally represented using respective orthogonal bases. In particular, the present paper investigates generalized polynomial chaos bases for the stochastic dimension and eigenfunction bases for the spatial dimension. Dynamic orthogonality is used to derive closed-form equations for the time evolution of mean, spatial and the stochastic fields. The resultant system of equations consists of a partial differential equation (PDE) that defines the dynamic evolution of the mean, a set of PDEs to define the time evolution of eigenfunction bases, while a set of ordinary differential equations (ODEs) define dynamics of the stochastic field. This system of dynamic evolution equations efficiently propagates the prior parametric uncertainty to the system response. The resulting bi-orthogonal expansion of the system response is used to reformulate the Bayesian inference for efficient exploration of the posterior distribution. The efficacy of the proposed method is investigated for calibration of a 2D transient diffusion simulator with an uncertain source location and diffusivity. The computational efficiency of the method is demonstrated against a Monte Carlo method and a generalized polynomial chaos approach.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2017, 27, 2; 229-243
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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