Applied Mathematics

Applied Mathematics

ISSN Print: 2152-7385
ISSN Online: 2152-7393
www.scirp.org/journal/am
E-mail: am@scirp.org
"Artificial Neural Networks Approach for Solving Stokes Problem"
written by Modjtaba Baymani, Asghar Kerayechian, Sohrab Effati,
published by Applied Mathematics, Vol.1 No.4, 2010
has been cited by the following article(s):
  • Google Scholar
  • CrossRef
[1] Conformable Fractional Models of the Stellar Helium Burning via Artificial Neural Networks
2021
[2] Analytical and numerical solution of differential equations with generalized fuzzy derivative
2020
[3] Numerical and theoretical analysis of neural networks to solve differential equations
2020
[4] Efficient Design of Neural Networks for Solving Third Order Partial Differential Equations
2020
[5] Finding Multiple Solutions of ODEs with Neural Networks.
2020
[6] Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
2020
[7] Finding multiple solutions of odes with neural networks
2020
[8] Solving Differential Equations Using Neural Network Solution Bundles
2020
[9] Polynomial Neural Networks and Taylor maps for Dynamical Systems Simulation and Learning
2019
[10] Learning From the von Kármán Vortex Street
2019
[11] Massive computational acceleration by using neural networks to emulate mechanism-based biological models
2019
[12] Learning to Optimize Multigrid PDE Solvers
2019
[13] Sensitivity analysis and performance evaluation of the PEMFC using wave-like porous ribs
2019
[14] NUMERICAL SOLUTION OF FIRST ORDER INITIAL VALUE PROBLEMS BY CROSSBRED NEURAL NETWORKS
2019
[15] Solution of two-point fuzzy boundary value problems by fuzzy neural networks
2019
[16] Matrix Lie Maps and Neural Networks for Solving Differential Equations
2019
[17] New Numerical Approach for Solving Fuzzy Boundary Value Problems
2019
[18] Poisson CNN: Convolutional Neural Networks for the Solution of the Poisson Equation with Varying Meshes and Dirichlet Boundary Conditions
2019
[19] DESIGN SUITABLE FEED FORWARD NEURAL NETWORK TO SOLVE TROESCH'S PROBLEM
Sci.Int.(Lahore), 2019
[20] NEURAL NETWORK METHOD OF RESTORING AN INITIAL PROFILE OF THE SHOCK WAVE
2018
[21] Deep Learning for Computational Science and Engineering
2018
[22] Deep Learning for Partial Differential Equations (PDEs)
2018
[23] Deep Learning of Turbulent Scalar Mixing
2018
[24] Numerical Approximation of Blow Forming Hyperelastic D Printed Preforms
2018
[25] Fully Fuzzy Neural Network For Solving Fuzzy Differential Equations
2018
[26] COMP535: Approximating PDEs Using Neural Networks–Applied to Navier-Stokes Equations
2018
[27] Artificial Neural Network for Solving Fuzzy Differential Equations under Generalized H–Derivation
2017
[28] Use of artificial neural network to predict pressure drop in rough pipes
2017
[29] Approximate Solutions to Poisson Equation Using Least Squares Support Vector Machines
Boundary and Interior Layers, Computational and Asymptotic Methods BAIL 2016, 2017
[30] Solving Level Set Evolving Using Fully Convolution Network
2017
[31] Approximate Solutions of Initial Value Problems for Ordinary Differential Equations Using Radial Basis Function Networks
Neural Processing Letters, 2017
[32] A deep learning framework for causal shape transformation
Neural Networks, 2017
[33] 吴自库; 许海洋; 李福乐
2016
[34] Deep Action Sequence Learning for Causal Shape Transformation
arXiv preprint arXiv:1605.05368, 2016
[35] Deep learning for decision making and autonomous complex systems
ProQuest Dissertations Publishing, 2016
[36] 一维热传导方程热源反问题基于最小二乘法的正则化方法
2016
[37] Aplicação de inteligência artificial em modelagem científica
2016
[38] 一维对流扩散方程逆过程 LS-SVM 解
黑龙江大学自然科学学报, 2016
[39] Approximate solutions to one-dimensional backward heat conduction problem using least squares support vector machines
2016
[40] DNS of turbulent flows using Artificial Neural Networks (ANNs)
2015
[41] A CNN-based approach for a class of non-standard hyperbolic partial differential equations modeling distributed parameters (nonlinear) control systems
Neurocomputing, 2015
[42] Numerical Solution of Partial Differential Equations by using Modified Artificial Neural Network
Network and Complex Systems, 2015
[43] Hierarchical Feature Extraction for Efficient Design of Microfluidic Flow Patterns
Proceedings of The 1st International Workshop on “Feature Extraction: Modern Questions and Challenges”, NIPS, 2015
[44] A CNN based approach for solving a hyperbolic PDE arising from a system of conservation laws-the case of the overhead crane
Advances in Computational Intelligence, 2013
[45] SUPPLEMENTARY INFORMATION: In
2010
[46] SUPPLEMENTARY INFORMATION TO THE
[47] Artificial Neural Networks for Flow Field Inference
[48] Tatiana A. Shemyakina1, Dmitriy A. Tarkhov1, Alexandra R. Beliaeva1, Ildar U. Zulkarnay2 1 Peter the Great St. Petersburg Polytechnic University, St …
Free SCIRP Newsletters
Copyright © 2006-2022 Scientific Research Publishing Inc. All Rights Reserved.
Top