Generalized conditional symmetry enhanced physics-informed neural network and application to the forward and inverse problems of nonlinear diffusion equations-Reference-Cited by-同舟云学术

Generalized conditional symmetry enhanced physics-informed neural network and application to the forward and inverse problems of nonlinear diffusion equations

Published:2023-03 Issue: Volume:168 Page:113169
ISSN:0960-0779
Container-title:Chaos, Solitons & Fractals
language:en
Short-container-title:Chaos, Solitons & Fractals

Author:

Zhang Zhi-Yong,Zhang Hui,Liu Ye,Li Jie-Ying,Liu Cheng-Bao

Funder

Minzu University of China

National Natural Science Foundation of China

Natural Science Foundation of Beijing Municipality

Publisher

Elsevier BV

Subject

General Mathematics,General Physics and Astronomy,Statistical and Nonlinear Physics,Applied Mathematics

Reference36 articles.

1. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations;Raissi;J Comput Phys,2019

2. Adam: A method for stochastic optimization;Kingma,2014

3. On the limited memory BFGS method for large scale optimization;Liu;Math Program,1989

4. Large sample properties of simulations using latin hypercube sampling;Stein;Technometrics,1987

5. Physics-informed neural networks with hard constraints for inverse design;Lu;SIAM J Sci Comput,2021

Cited by 9 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. On the development of steady-state and dynamic mass-constrained neural networks using noisy transient data;Computers & Chemical Engineering;2024-08

2. Multi-parallelized PINNs for the inverse problem study of NLS typed equations in optical fiber communications: Discovery on diverse high-order terms and variable coefficients;Chaos, Solitons & Fractals;2024-04

3. Rolling theory-guided prediction of hot-rolled plate width based on parameter transfer strategy;ISA Transactions;2024-03

4. Physics-Informed Neural Network (PINN) for Solving Frictional Contact Temperature and Inversely Evaluating Relevant Input Parameters;Lubricants;2024-02-17

5. Physics-Informed Neural Network for Analyzing the Key Performance of Coaxial Magnetic Gear;2024