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科研机构
数学与系统科学研究... [10]
力学研究所 [1]
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期刊论文 [11]
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2024 [1]
2022 [4]
2021 [5]
2020 [1]
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Stochastic dynamics of aircraft ground taxiing via improved physics-informed neural networks
期刊论文
NONLINEAR DYNAMICS, 2024, 页码: 16
作者:
Zhang, Ying
;
Jin, Zhengrong
;
Wang L(王笼)
;
Zheng, Kaixin
;
Jia, Wantao
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2024/02/19
PINNs
Aircraft ground taxiing model
Fokker-Planck equations
Inverse problem
Data-driven rogue waves and parameters discovery in nearly integrable PT-symmetric Gross-Pitaevskii equations via PINNs deep learning
期刊论文
PHYSICA D-NONLINEAR PHENOMENA, 2022, 卷号: 439, 页码: 12
作者:
Zhong, Ming
;
Gong, Shibo
;
Tian, Shou-Fu
;
Yan, Zhenya
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2023/02/07
GeneralizedGrossPitaevskiiequation
ComplexPT-symmetricpotentials
Physics-informeddeepneuralnetworks
Data-driven rogue waves and parameters discovery discovery
DRVN (deep random vortex network): A new physics-informed machine learning method for simulating and inferring incompressible fluid flows
期刊论文
PHYSICS OF FLUIDS, 2022, 卷号: 34, 期号: 10, 页码: 21
作者:
Zhang, Rui
;
Hu, Peiyan
;
Meng, Qi
;
Wang, Yue
;
Zhu, Rongchan
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2023/02/07
Monte Carlo fPINNs: Deep learning method for forward and inverse problems involving high dimensional fractional partial differential equations
期刊论文
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 卷号: 400, 页码: 17
作者:
Guo, Ling
;
Wu, Hao
;
Yu, Xiaochen
;
Zhou, Tao
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2023/02/07
Physics -informed neural networks
Fractional Laplacian
Nonlocal operators
Uncertainty quantification
Data-Driven Deep Learning for The Multi-Hump Solitons and Parameters Discovery in NLS Equations with Generalized PT-Scarf-II Potentials
期刊论文
NEURAL PROCESSING LETTERS, 2022, 页码: 19
作者:
Zhong, Ming
;
Zhang, Jian-Guo
;
Zhou, Zijian
;
Tian, Shou-Fu
;
Yan, Zhenya
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2023/02/07
Focusing and defocusing nonlinear Schrodinger equations
Generalized PT-Scarf-II potential
Physics-informed deep neural networks
Data-driven solitons and parameters discovery
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
作者:
Wang, Li
;
Yan, Zhenya
收藏
  |  
浏览/下载:2/0
  |  
提交时间: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
作者:
Zhou, Zijian
;
Yan, Zhenya
收藏
  |  
浏览/下载:5/0
  |  
提交时间: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
作者:
Zhou,Zijian
;
Yan,Zhenya
收藏
  |  
浏览/下载:4/0
  |  
提交时间: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
作者:
Wang, Li
;
Yan, Zhenya
收藏
  |  
浏览/下载:23/0
  |  
提交时间: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
作者:
Zhou, Zijian
;
Yan, Zhenya
收藏
  |  
浏览/下载:36/0
  |  
提交时间: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
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