ListarInstitute of New Imaging Technologies (INIT) por tema "uncertainty quantification"
Mostrando ítems 1-7 de 7
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A survey on uncertainty quantification in deep learning for financial time series prediction
Elsevier Science Direct (2024-01-28)Investors make decisions about buying and selling a financial asset based on available information. The traditional approach in Deep Learning when trying to predict the behavior of an asset is to take a price history, train ... -
Improving the Approximation of the First- and Second-Order Statistics of the Response Stochastic Process to the Random Legendre Differential Equation
Springer Nature Switzerland AG (2019-04-16)In this paper, we deal with uncertainty quantification for the random Legendre differential equation, with input coefficient A and initial conditions X0 and X1. In a previous study (Calbo et al. in Comput Math Appl ... -
Lp-calculus Approach to the Random Autonomous Linear Differential Equation with Discrete Delay
Springer Nature Switzerland AG (2019-06-19)In this paper, we provide a full probabilistic study of the random autonomous linear differential equation with discrete delay τ > 0: x (t) = ax(t) + bx(t − τ ), t ≥ 0, with initial condition x(t) = g(t), −τ ≤ t ≤ 0. ... -
On the convergence of adaptive gPC for non-linear random difference equations: Theoretical analysis and some practical recommendations
International Scientific Research Publications (2018-06-19)In this paper, the application of adaptive generalized polynomial chaos (gPC) to quantify the uncertainty for non-linear random difference equations is analyzed. It is proved in detail that, under certain assumptions, the ... -
Random non-autonomous second order linear differential equations: mean square analytic solutions and their statistical properties
Springer (2018-10-24)In this paper we study random non-autonomous second order linear differential equations by taking advantage of the powerful theory of random difference equations. The coefficients are assumed to be stochastic processes, ... -
Some Notes to Extend the Study on Random Non-Autonomous Second Order Linear Differential Equations Appearing in Mathematical Modeling
MDPI (2018-11-27)The objective of this paper is to complete certain issues from our recent contribution (Calatayud, J.; Cortés, J.-C.; Jornet, M.; Villafuerte, L. Random non-autonomous second order linear differential equations: mean ... -
Uncertainty quantification for random parabolic equations with nonhomogeneous boundary conditions on a bounded domain via the approximation of the probability density function
John Wiley & Sons, Ltd. (2018-11-14)This paper deals with the randomized heat equation defined on a general bounded interval [L1, L2] and with nonhomogeneous boundary conditions. The solution is a stochastic process that can be related, via changes of variable, ...