PINN deep learning method for the Chen–Lee–Liu equation: Rogue wave on the periodic background

We consider the exact rogue periodic wave (rogue on background) and solutions for Chen–Lee–Liu equation via odd-th order Darboux transformation. Then, multi-layer physics-informed neural networks (PINNs) deep learning method is applied to research data-driven wave, breather soliton of well-known equation. Especially, learned first time solve partial differential In addition, using image simulation, relevant dynamical behaviors error analysis there are presented. The numerical results indicate that can be generated well by PINNs method.