Listar Modelos e métodos numéricos en enxeñaría e ciencias aplicadas (M2NICA) por data de publicación
Mostrando ítems 41-60 de 95
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The stochastic collocation Monte Carlo sampler: highly efficient sampling from ‘expensive’ distributions
(Taylor and Francis Group & Routledge, 2019)[Abstract]: In this article, we propose an efficient approach for inverting computationally expensive cumulative distribution functions. A collocation method, called the Stochastic Collocation Monte Carlo sampler (SCMC ... -
Numerical approximations of McKean anticipative backward stochastic differential equations arising in initial margin requirements
(EDP Science, 2019-04-02)[Abstract]: We introduce a new class of anticipative backward stochastic differential equations with a dependence of McKean type on the law of the solution, that we name MKABSDE. We provide existence and uniqueness results ... -
Quasi-Regression Monte-Carlo Scheme for Semi-Linear PDEs and BSDEs with Large Scale Parallelization on GPUs
(Springer, 2019-04-04)[Abstract]: In this article we design a novel quasi-regression Monte Carlo algorithm in order to approximate the solution of discrete time backward stochastic differential equations, and we analyze the convergence of the ... -
Quasi-Regression Monte-Carlo Method for Semi-Linear PDEs and BSDEs
(MDPI AG, 2019-08-06)[Abstract] In this work we design a novel and efficient quasi-regression Monte Carlo algorithm in order to approximate the solution of discrete time backward stochastic differential equations (BSDEs), and we analyze the ... -
Transient hysteresis and inherent stochasticity in gene regulatory networks
(Nature Publishing Group, 2019-10-08)[Abstract] Cell fate determination, the process through which cells commit to differentiated states is commonly mediated by gene regulatory motifs with mutually exclusive expression states. The classical deterministic ... -
A New Technique for Improved Use of Thermal Energy from Waste Effluents
(MDPI AG, 2020-01-09)[Abstract] Energy sustainability and environmental protection in general are at the heart of engineering and industry discussions. Countless efforts have been devoted to improving the energy efficiency of industrial processes ... -
Global optimization for data assimilation in landslide tsunami models
(Elsevier, 2020-02-15)[Abstract]: The goal of this article is to make automatic data assimilation for a landslide tsunami model, given by the coupling between a non-hydrostatic multi-layer shallow-water and a Savage-Hutter granular landslide ... -
On an adaptive stabilized mixed finite element method for the Oseen problem with mixed boundary conditions
(Elsevier BV, 2020-06-15)[Abstract] We consider the Oseen problem with nonhomogeneous Dirichlet boundary conditions on a part of the boundary and a Neumann type boundary condition on the remaining part. Suitable least squares terms that arise from ... -
Computation of Resonance Modes in Open Cavities with Perfectly Matched Layers
(MDPI AG, 2020-08-18)[Abstract] During the last decade, several authors have addressed that the Perfectly Matched Layers (PML) technique can be used not only for the computation of the near-field in time-dependent and time-harmonic scattering ... -
European and American Options Valuation by Unsupervised Learning with Artificial Neural Networks
(MDPI AG, 2020-08-19)[Abstract] Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). In this work, the classical problem of pricing European and American financial options, based ... -
Numerical Simulation of a Nonlinear Problem Arising in Heat Transfer and Magnetostatics
(MDPI AG, 2020-08-19)[Abstract] We present a numerical model that comprises a nonlinear partial differential equation. We apply an adaptive stabilised mixed finite element method based on an a posteriori error indicator derived for this ... -
Machine Learning to Compute Implied Volatility from European/American Options Considering Dividend Yield
(MDPI AG, 2020-09-15)[Abstract] Computing implied volatility from observed option prices is a frequent and challenging task in finance, even more in the presence of dividends. In this work, we employ a data-driven machine learning approach ... -
A Two-Dimensional Multi-Species Model for Different Listeria Monocytogenes Biofilm Structures and Its Numerical Simulation
(Elsevier BV, 2020-11-01)[Abstract] In this work we propose a two-dimensional multi-species model to describe the dynamics of biofilms formed by the pathogenic bacteria Listeria monocytogenes. Different Listeria monocytogenes strains produce ... -
Financial Option Valuation by Unsupervised Learning with Artificial Neural Networks
(MDPI AG, 2020-12-28)[Abstract] Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). The classical problem of pricing European and American financial options, based on the corresponding ... -
Upwind Finite Element-PML Approximation of a Novel Linear Potential Model for Free Surface Flows Produced by a Floating Rigid Body
(Elsevier, 2021)[Abstract] A novel linear potential model is presented to compute free surface flows of incompressible fluids produced by the motion of a floating rigid body in the presence of an underlying non-uniform flow. In particular, ... -
Deep Learning-Based Method for Computing Initial Margin †
(MDPI, 2021)[Abstract] Following the guidelines of the Basel III agreement (2013), large financial institutions are forced to incorporate additional collateral, known as Initial Margin, in their transactions in OTC markets. Currently, ... -
On the Adaptive Numerical Solution to the Darcy–Forchheimer Model †
(MDPI, 2021)[Abstract] We considered a primal-mixed method for the Darcy–Forchheimer boundary value problem. This model arises in fluid mechanics through porous media at high velocities. We developed an a posteriori error analysis of ... -
Quantum Arithmetic for Directly Embedded Arrays
(MDPI, 2021)[Abstract] We describe a general-purpose framework to implement quantum algorithms relying upon an efficient handling of arrays. The cornerstone of the framework is the direct embedding of information into quantum amplitudes, ... -
Numerical Solution of a Nonlinear PDE Model for Pricing Renewable Energy Certificates (RECs)
(Elsevier, 2021)[Abstract] In this article we present a valuation method for Renewable Energy Certificates (RECs) or green certificates. For this purpose, we propose a non-linear PDE model with two stochastic factors: the accumulated green ... -
PDE Models for the Pricing of a Defaultable Coupon-Bearing Bond Under an Extended JDCEV Model
(Elsevier, 2021)[Abstract] We consider a two-factor model for the pricing of a non callable defaultable bond which pays coupons at certain given dates. The model under consideration is the Jump to Default Constant Elasticity of Variance ...