Results 31 to 40 of about 10,662,604 (380)

A modular three-dimensional finite-difference ground-water flow model

, 1984
A computer program for simulating ground-water flow in three dimensions is presented. This report includes detailed explanations of physical and mathematical concepts on which the model is developed.
M. G. McDonald, A. W. Harbaugh
semanticscholar   +1 more source

Non-standard and Numerov finite difference schemes for finite difference time domain method to solve one-dimensional Schrödinger equation

Journal of Physics: Theories and Applications, 2018
The purpose of  this paper is to show some improvements of the finite-difference time domain (FDTD) method using Numerov and non-standard finite difference (NSFD) schemes for solving the one-dimensional Schrödinger equation.
Lily Maysari Angraini, I Wayan Sudiarta
doaj   +1 more source

A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation [PDF]

Annual Conference Computational Learning Theory, 2018
Temporal difference learning (TD) is a simple iterative algorithm widely used for policy evaluation in Markov reward processes. Bhandari et al. prove finite time convergence rates for TD learning with linear function approximation.
Jalaj Bhandari, Daniel Russo, Raghav Singal   +2 more
semanticscholar   +1 more source

Approximating the total variation with finite differences or finite elements [PDF]

, 2021
à paraitre; International audience; We present and compare various types of discretizations which have been proposed to approximate the total variation (mostly, of a grey-level image in two dimensions). We discuss the properties of finite differences and finite elements based approach and compare their merits, in particular in terms of error estimates ...
Chambolle, Antonin, Pock, Thomas
openaire   +4 more sources

Finite logarithmic order meromorphic solutions of linear difference/differential-difference equations [PDF]

Mathematica Bohemica
Firstly we study the growth of meromorphic solutions of linear difference equation of the form A_k(z)f(z+c_k)+\cdots+A_1(z)f(z+c_1)+A_0(z)f(z)=F(z), where $A_k(z),\ldots,A_0(z)$ and $F(z)$ are meromorphic functions of finite logarithmic order, $c_i$
Abdelkader Dahmani, Benharrat Belaïdi
doaj   +1 more source

Unconditionally positive finite difference and standard explicit finite difference schemes for power flow equation [PDF]

The University Thought: Publication in Natural Sciences, 2019
Power flow equation for step-index glass optical fiber was solved using recently reported unconditionally-positive finite difference (UPFD) scheme. Solution obtained using UPFD scheme was compared with solution obtained using standard explicit finite ...
Drljača Branko, Savović Svetislav
doaj  

Elastic Reverse-Time Migration with Complex Topography

Energies, 2021
Migration is an important step in seismic data processing for oil and gas exploration. The accuracy of migration directly affects the accuracy of subsequent oil and gas reservoir characterization.
Yu Zhong, Hanming Gu, Yangting Liu, Qinghui Mao   +3 more
doaj   +1 more source

A 2D Moving Mesh Finite Element Analysis of Heat Transfer in Arctic Soils

Thermo, 2023
Accurate soil heat transfer models are needed to predict and adapt to a warming arctic. A numerical model to accurately predict temperatures and thaw depths in soils, both with depth and with horizontal distance from features such as cliffs, was ...
Michelle Wilber, Getu Hailu
doaj   +1 more source

A Robust Bubble Growth Solution Scheme for Implementation in CFD Analysis of Multiphase Flows

Computation, 2023
Although the full form of the Rayleigh–Plesset (RP) equation more accurately depicts the bubble behavior in a cavitating flow than its reduced form, it finds much less application than the latter in the computational fluid dynamic (CFD) simulation due to
Hao Pang, Gracious Ngaile
doaj   +1 more source

Modifying Explicit Finite Difference Method by Using Radial Basis Function Neural Network [PDF]

Al-Rafidain Journal of Computer Sciences and Mathematics, 2013
In this research, we use artificial neural networks, specifically radial basis function neural network (RBFNN) to improve the performance and work of the explicit finite differences method (EFDM), where it was compared, the modified method with an ...
Omar Kasim
doaj   +1 more source