Results 21 to 30 of about 2,026 (229)
Structured Random Sketching for PDE Inverse Problems [PDF]
For an overdetermined system $\mathsf{A}\mathsf{x} \approx \mathsf{b}$ with $\mathsf{A}$ and $\mathsf{b}$ given, the least-square (LS) formulation $\min_x \, \|\mathsf{A}\mathsf{x}-\mathsf{b}\|_2$ is often used to find an acceptable solution $\mathsf{x}$.
Ke Chen +3 more
openaire +3 more sources
Derivatives in time of higher order (more than two) arise in various fields such as acoustics, medical ultrasound, viscoelasticity and thermoelasticity.
M.J. Huntul, I. Tekin
doaj +1 more source
Inverse Source Problems for Degenerate Time-Fractional PDE [PDF]
12 pages, 8 ...
Al-Salti, Nasser, Karimov, Erkinjon
openaire +2 more sources
PINNs algorithm and its application in geotechnical engineering
The physical information neural networks (PINNs) algorithm, a new mesh-free algorithm, uses the automatic differential method to embed the partial differential equation directly into the neural networks so as to realize the intelligent solution of the ...
LAN Peng 1, LI Hai-chao 1, YE Xin-yu 1, ZHANG Sheng 1, SHENG Dai-chao 1, 2
doaj +1 more source
A deep neural network approach for parameterized PDEs and Bayesian inverse problems
We consider the simulation of Bayesian statistical inverse problems governed by large-scale linear and nonlinear partial differential equations (PDEs). Markov chain Monte Carlo (MCMC) algorithms are standard techniques to solve such problems.
Harbir Antil +3 more
doaj +1 more source
An efficient algorithm for some highly nonlinear fractional PDEs in mathematical physics. [PDF]
In this paper, a fractional complex transform (FCT) is used to convert the given fractional partial differential equations (FPDEs) into corresponding partial differential equations (PDEs) and subsequently Reduced Differential Transform Method (RDTM) is ...
Jamshad Ahmad, Syed Tauseef Mohyud-Din
doaj +1 more source
DISCRETE NON-STANDARD FORMULATION OF PDE INVERSE PROBLEMS
Abstract In this paper, we are interested in the computation of the unknown initial state for the simulation and prediction of PDE systems where the solution measures are partially known over a time interval. Such a problem is usually solved by an ill-posed optimal control problem.
Cyr S. Ngamouyih Moussata +3 more
openaire +2 more sources
Numerical methods, such as finite element or finite difference, have been widely used in the past decades for modeling solid mechanics problems by solving partial differential equations (PDEs).
Yawen Deng +5 more
doaj +1 more source
On an inverse problem for a nonlinear third order in time partial differential equation
In this article, first we convert an inverse problem of determining the unknown timewise terms of nonlinear third order in time partial differential equation (PDE) from knowledge of two boundary measurements to the auxiliary system of integral equations.
M.J. Huntul, I. Tekin
doaj +1 more source
FDM data driven U-Net as a 2D Laplace PINN solver
Efficient solution of partial differential equations (PDEs) of physical laws is of interest for manifold applications in computer science and image analysis. However, conventional domain discretization techniques for numerical solving PDEs such as Finite
Anto Nivin Maria Antony +2 more
doaj +1 more source

