Numerical solution of several kinds of differential equations using block neural network method with improved extreme learning machine algorithm-Reference-Cited by-同舟云学术

Numerical solution of several kinds of differential equations using block neural network method with improved extreme learning machine algorithm

Published:2020-03-04 Issue:3 Volume:38 Page:3445-3461
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Yang Yunlei¹,Hou Muzhou²,Luo Jianshu³,Tian Zhongchu⁴

Affiliation:

1. School of Mathematics and Statistics, Guizhou University, Guiyang, China

2. School of Mathematics and Statistics, Central South University, Changsha, China

3. High-tech Research Institute, Hunan Institute of Traffic Engineering, Hengyang, China

4. School of Civil Engineering, Changsha University of Science and Technology, Changsha, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference29 articles.

1. K.S. Mcfall , An artificial neural network method for solving boundary value problems with arbitrary irregular boundaries, Ph.D. thesis, Georgia Institute of Technology (2006).

2. Numerical solution of the nonlinear Schrodinger equation by feedforward neural networks;Shirvany;Commun Nonlinear Sci Numer Simul,2008

3. N. Yadav , A. Yadav and K. Deep , Artificial neural network technique for solution of nonlinear elliptic boundary value problems, in Proceedings of Fourth International Conference on Soft Computing for Problem Solving, Advances in Intelligent Systems and Computing 335 (2015) 113–121.

4. Solving differential equations with constructed neural Networks;Tsoulos;Neurocomputing,2009

5. Two coupled neural network based solution of the Hamilton-Jacobi-Bellman equation;Masmoudi;Appl Soft Comput,2011

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Numerical solution of ruin probability of continuous time model based on optimal adaptive particle swarm optimization-triangular neural network algorithm;Soft Computing;2023-08-03

2. M-WDRNNs: Mixed-Weighted Deep Residual Neural Networks for Forward and Inverse PDE Problems;Axioms;2023-07-30

3. Numerical solving for generalized Black-Scholes-Merton model with neural finite element method;Digital Signal Processing;2022-11

4. Exponential Basis Approximated Fuzzy Components High-Resolution Compact Discretization Technique for 2D Convection–Diffusion Equations;Differential Equations and Dynamical Systems;2022-10-01

5. An Investigation of Approximate Solutions for Second Order Ordinary Differential Equations using Sigmoid-Weighted Neural Networks;International Journal of Applied and Computational Mathematics;2022-04-15