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Browsing by Subject "Uncertainty quantification"

Now showing items 21-32 of 32

On the convergence of adaptive gPC for non-linear random difference equations: Theoretical analysis and some practical recommendations

Calatayud-Gregori, Julia; Cortés, J.-C.; Jornet-Sanz, Marc (International Scientific Research Publications MY SDN. BHD., 2018)

[EN] 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, ...
On the Legendre differential equation with uncertainties at the regular-singular point 1: Lp random power series solution and approximation of its statistical moments

Calatayud-Gregori, Julia; Cortés, J.-C.; Jornet-Sanz, Marc (John Wiley & Sons, 2019-07)

[EN] In this paper, we construct two linearly independent response processes to the random Legendre differential equation on (-1,1)U(1,3), consisting of Lp(omega) convergent random power series around the regular¿singular ...
Probabilistic analysis of linear-quadratic logistic-type models with hybrid uncertainties via probability density functions

Burgos-Simon, Clara; Cortés, J.-C.; López-Navarro, Elena; Villanueva Micó, Rafael Jacinto (American Institute of Mathematical Sciences, 2021-03-02)

[EN] We provide a full stochastic description, via the first probability density function, of the solution of linear-quadratic logistic-type differential equation whose parameters involve both continuous and discrete random ...
Probabilistic study of the effect of anti-epileptic drugs under uncertainty: Cost-effectiveness analysis

Barrachina Martínez, Isabel; Navarro-Quiles, Ana; Ramos, Marta; Romero, José-Vicente; Roselló, María-Dolores; Vivas-Consuelo, David (MDPI AG, 2020-07)

[EN] Epilepsy is one of the most ancient diseases. Despite the efforts of scientists and doctors to improve the quality of live of epileptic patients, the disease is still a mystery in many senses. Anti-epileptic drugs are ...
Second order linear differential equations with analytic uncertainties: stochastic analysis via the computation of the probability density function

Jornet, Marc; Calatayud, J.; Le Maître, O.P.; Cortés, J.-C. (Elsevier, 2020-08-15)

[EN] This paper concerns the analysis of random second order linear differential equations. Usually, solving these equations consists of computing the first statistics of the response process, and that task has been an ...
Some notes to extend the study on random non-autonomous second order linear differential equations appearing in Mathematical Modeling

Calatayud-Gregori, Julia; Cortés, J.-C.; Jornet-Sanz, Marc (MDPI AG, 2018)

[EN] 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: ...
Uncertainty Assessment of Proarrhythmia Predictions Derived from Multi-Level in Silico Models

Kopanska, Karolina; Rodríguez-Belenguer, Pablo; Llopis-Lorente, Jordi; Trénor, Beatriz; Saiz, Javier; Pastor, Manuel (Universitat Politècnica de València, 2023-02-14)

[EN] These datasets were generated to train ("PopulationDrugsTrainingKrNaLCaL.xlsx") and test ("PopulationDrugsTestKrCaLNaL.xlsx") the uncertainty assessment models developed in the paper "Uncertainty assessment of ...
Uncertainty quantification for hybrid random logistic models with harvesting via density functions

Cortés, J.-C.; Moscardó-García, A.; Villanueva Micó, Rafael Jacinto (Elsevier, 2022-02)

[EN] The so-called logistic model with harvesting, p '(t)=rp(t)(1-p(t)/K)-c(t)p(t), p(t(0))=p(0), is a classical ecological model that has been extensively studied and applied in the deterministic setting. It has also been ...
Uncertainty quantification for nonlinear difference equations with dependent random inputs via a stochastic Galerkin projection technique

Calatayud-Gregori, Julia; Cortés, J.-C.; Jornet-Sanz, Marc (Elsevier, 2019-06-30)

[EN] Discrete stochastic systems model discrete response data on some phenomenon with inherent uncertainty. The main goal of uncertainty quantification is to derive the probabilistic features of the stochastic system. This ...
Uncertainty quantification for random parabolic equations with non-homogeneous boundary conditions on a bounded domain via the approximation of the probability density function

Calatayud-Gregori, Julia; Cortés, J.-C.; Jornet-Sanz, Marc (John Wiley & Sons, 2019-11-30)

[EN] This paper deals with the randomized heat equation defined on a general bounded interval [L-1, L-2] and with nonhomogeneous boundary conditions. The solution is a stochastic process that can be related, via changes ...
Uncertainty quantification in dynamical models. An application to cocaine consumption in Spain

Rubio Monzó, María (Universitat Politècnica de València, 2015-10-13)

[EN] The present Ph.D. Thesis considers epidemiological mathematical models based on ordinary differential equations and shows its application to understand the cocaine consumption epidemic in Spain. Three mathematical ...
Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions

Bevia-Escrig, Vicente-José; Burgos-Simon, Clara; Cortés, J.-C.; Villanueva Micó, Rafael Jacinto (MDPI AG, 2021-06)

[EN] The Baranyi-Roberts model describes the dynamics of the volumetric densities of two interacting cell populations. We randomize this model by considering that the initial conditions are random variables whose distributions ...