The nonlinear wave solutions and parameters discovery of the Lakshmanan-Porsezian-Daniel based on deep learning
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Publication:2113140
DOI10.1016/j.chaos.2022.112155zbMath1505.35332OpenAlexW4229061142MaRDI QIDQ2113140
Publication date: 12 January 2023
Published in: Chaos, Solitons and Fractals (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.chaos.2022.112155
converted wavesdeep learningdata-driven solutionsLakshmanan-Porsezian-Daniel modelparameters discovery
Learning and adaptive systems in artificial intelligence (68T05) PDEs in connection with optics and electromagnetic theory (35Q60) Lasers, masers, optical bistability, nonlinear optics (78A60) Traveling wave solutions (35C07)
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Dynamic analysis on optical pulses via modified PINNs: soliton solutions, rogue waves and parameter discovery of the CQ-NLSE, Exact solutions and Darboux transformation for the reverse space-time nonlocal Lakshmanan-Porsezian-Daniel equation, Pre-training physics-informed neural network with mixed sampling and its application in high-dimensional systems
Uses Software
Cites Work
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- Waves that appear from nowhere and disappear without a trace
- On the limited memory BFGS method for large scale optimization
- Nonlinear optical waves
- Multilayer feedforward networks are universal approximators
- PINN deep learning method for the Chen-Lee-Liu equation: rogue wave on the periodic background
- Data-driven peakon and periodic peakon solutions and parameter discovery of some nonlinear dispersive equations via deep learning
- B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data
- The data-driven localized wave solutions of the derivative nonlinear Schrödinger equation by using improved PINN approach
- Physics-informed semantic inpainting: application to geostatistical modeling
- A two-stage physics-informed neural network method based on conserved quantities and applications in localized wave solutions
- Predicting the dynamic process and model parameters of the vector optical solitons in birefringent fibers \textit{via} the modified PINN
- Data-driven vector soliton solutions of coupled nonlinear Schrödinger equation using a deep learning algorithm
- Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
- Lump solutions to the Kadomtsev-Petviashvili equation
- Propagation of dispersion–nonlinearity-managed solitons in an inhomogeneous erbium-doped fiber system
- Large Sample Properties of Simulations Using Latin Hypercube Sampling
- An exact solution for a derivative nonlinear Schrödinger equation
- A Two-dimensional Boussinesq equation for water waves and some of its solutions
- Method for Solving the Korteweg-deVries Equation
- High-dimensional nonlinear wave transitions and their mechanisms
- On the integrability aspects of the one-dimensional classical continuum isotropic biquadratic Heisenberg spin chain
- Controllable pulse width of bright similaritons in a tapered graded index diffraction decreasing waveguide
- Moving breathers and breather-to-soliton conversions for the Hirota equation
- Exact envelope-soliton solutions of a nonlinear wave equation
- Schrödinger ordinary solitons and chirped solitons: fourth-order dispersive effects and cubic-quintic nonlinearity
- Solving second-order nonlinear evolution partial differential equations using deep learning