Pages that link to "Item:Q2113135"
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The following pages link to Prediction of optical solitons using an improved physics-informed neural network method with the conservation law constraint (Q2113135):
Displaying 5 items.
- Data-driven prediction of soliton solutions of the higher-order NLSE via the strongly-constrained PINN method (Q2107164) (← links)
- Spatiotemporal dynamics on a class of \((n+1)\)-dimensional reaction-diffusion neural networks with discrete delays and a conical structure (Q2680065) (← links)
- A dimension-augmented physics-informed neural network (DaPINN) with high level accuracy and efficiency (Q6095102) (← links)
- Two-stage initial-value iterative physics-informed neural networks for simulating solitary waves of nonlinear wave equations (Q6497269) (← links)
- Adaptive sampling physics-informed neural network method for high-order rogue waves and parameters discovery of the \((2+1)\)-dimensional CHKP equation (Q6554449) (← links)
