«random inverse partial differential equation»
۱۳۹ نتیجهSolving random inverse heat conduction problems using PSO and genetic algorithms
The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inve
Seminar & Events Bulletin: Differential Equations
Differential Equations Thursday, September 24, 2015, 4:00pm-5:00pm 4088 East Hall Zhiwu Lin (Georgia Tech) Instability index, exponential trichotomy and invariant manifolds for Hamiltonian PDEs Consider a general linear Hamiltonian system u_t = JLu in a Hilbert space X, called th
NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET Multivariate Gaussian Random Fields with Oscillating Covariance Functions using Systems of Stochastic Partial Differential Equations
In this paper we propose a new approach for constructing multivariate Gaussian random fields (GRFs) with oscillating covariance functions through systems of stochastic partial differential equations (SPDEs). We discuss how to build systems of SPDEs that introduces oscillation cha
Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models
We introduce in this work the normalizing field flows (NFF) for learning random fields from scattered measurements. More precisely, we construct a bijective transformation (a flow characterizing by neural networks) between Gaussian with Karhunen-Lo\`eve (KL) expansion structure a
Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems
This paper develops a class of meshless methods that are well-suited to statistical inverse problems involving partial differential equations (PDEs). The methods discussed in this paper view the forcing term in the PDE as a random field that induces a probability distribution ove
Monte Carlo fPINNs: Deep learning method for forward and inverse problems involving high dimensional fractional partial differential equations
We introduce a sampling based machine learning approach, Monte Carlo physics informed neural networks (MC-PINNs), for solving forward and inverse fractional partial differential equations (FPDEs). As generalization of (PINNs), our method relies on deep network surrogates in addit
On the calculation of Fisher information for quantum parameter estimation based on the stochastic master equation
The Fisher information can be used to indicate the precision of parameter estimation by the quantum Cramér-Rao inequality. This paper presents an efficient numerical algorithm for the calculation of Fisher information based on quantum weak measurement. According to the quantum st
SDEs driven by a time-changed Lévy process and their associated time-fractional order pseudo-differential equations
It is known that if a stochastic process is a solution to a classical Itô stochastic differential equation (SDE), then its transition probabilities satisfy in the weak sense the associated Cauchy problem for the forward Kolmogorov equation. The forward Kolmogorov equation is a pa
Simulating Solute Transport in Porous or Fractured Formations Using Random Walk Particle Tracking: A Review
Traditional Eulerian approaches to solute transport generally require very fine discretization of the transport Since the first attempts some 20 yr ago in the field of hydrology, domain to overcome recurrent problems of unstable nurandom walk (RW) particle tracking as applied to
Solitons in media with random dispersive perturbations
A statistical approach of the propagation of solitons in media with spatially random dispersive perturbations is developed. Applying the inverse scattering transform several regimes are put into evidence which are determined by the mass and the velocity of the incoming soliton an