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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：59/0  |  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：65/0  |  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：93/0  |  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