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Data-driven peakon and periodic peakon solutions and parameter discovery of some nonlinear dispersive equations via deep learning 期刊论文
PHYSICA D-NONLINEAR PHENOMENA, 2021, 卷号: 428, 页码: 15
Authors:  Wang, Li;  Yan, Zhenya
Favorite  |  View/Download:13/0  |  Submit date:2022/04/02
Nonlinear dispersive equation  Initial-boundary value conditions  Physics-informed neural networks  Deep learning  Data-driven peakon and periodic peakon  solutions Data-driven parameter discovery  
Deep learning neural networks for the third-order nonlinear Schrodinger equation: bright solitons, breathers, and rogue waves 期刊论文
COMMUNICATIONS IN THEORETICAL PHYSICS, 2021, 卷号: 73, 期号: 10, 页码: 9
Authors:  Zhou, Zijian;  Yan, Zhenya
Favorite  |  View/Download:11/0  |  Submit date:2022/04/02
third-order nonlinear Schrodinger equation  deep learning  data-driven solitons  data-driven parameter discovery  
Deep learning neural networks for the third-order nonlinear Schr?dinger equation: bright solitons, breathers, and rogue waves 期刊论文
Communications in Theoretical Physics, 2021, 卷号: 73, 期号: 10
Authors:  Zhou,Zijian;  Yan,Zhenya
Favorite  |  View/Download:17/0  |  Submit date:2022/04/02
third-order nonlinear Schr?dinger equation  deep learning  data-driven solitons  data-driven parameter discovery  
Data-driven rogue waves and parameter discovery in the defocusing nonlinear Schrodinger equation with a potential using the PINN deep learning 期刊论文
PHYSICS LETTERS A, 2021, 卷号: 404, 页码: 7
Authors:  Wang, Li;  Yan, Zhenya
Favorite  |  View/Download:28/0  |  Submit date:2021/10/26
Defocusing NLS equation with the  time-dependent potential  Initial-boundary value conditions  Physics-informed neural networks  Deep learning  Data-driven rogue waves and parameter discovery  
Solving forward and inverse problems of the logarithmic nonlinear Schrodinger equation with PT-symmetric harmonic potential via deep learning 期刊论文
PHYSICS LETTERS A, 2021, 卷号: 387, 页码: 12
Authors:  Zhou, Zijian;  Yan, Zhenya
Favorite  |  View/Download:32/0  |  Submit date:2021/04/26
Logarithmic nonlinear Schrodinger equation  PT-symmetric potentials  Physics-informed neural networks  Deep learning  Data-driven discovery of LNLS equation  Data-driven solitons  
SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems 期刊论文
NEURAL NETWORKS, 2020, 卷号: 132, 页码: 166-179
Authors:  Jin, Pengzhan;  Zhang, Zhen;  Zhu, Aiqing;  Tang, Yifa;  Karniadakis, George Em
Favorite  |  View/Download:46/0  |  Submit date:2021/04/26
Deep learning  Physics-informed  Dynamical systems  Hamiltonian systems  Symplectic maps  Symplectic integrators