activity
20202024
most citedPINN deep learning for the Chen-Lee-Liu equation: Rogue wave on the periodic background

131 citations · 268 across the 10 of their papers we have counts for

collaborators

10 papers

nlin.SI2024

Lax pairs informed neural networks solving integrable systems

Juncai Pu, Yong Chen

Lax pairs are one of the most important features of integrable system. In this work, we propose the Lax pairs informed neural networks (LPNNs) tailored for the integrable systems w…

physics.flu-dyn2023★ 40 cited

Complex dynamics on the one-dimensional quantum droplets via time piecewise PINNs

Juncai Pu, Yong Chen

The dynamics of one-dimensional quantum droplets and the landing applications of deep learning are recent research hotspots. In this work, we propose a novel time piecewise physics…

nlin.PS2022★ 1 cited

Data-driven forward-inverse problems for the variable coefficients Hirota equation using deep learning method

Huijuan Zhou, Juncai Pu, Yong Chen

Data-driven forward-inverse problems for the variable coefficients Hirota (VCH) equation are discussed in this paper. The main idea is to use the improved physics-informed neural n…

math.NA2021

Data-driven forward-inverse problems for Yajima-Oikawa system using deep learning with parameter regularization

Juncai Pu, Yong Chen

We investigate data-driven forward-inverse problems for Yajima-Oikawa (YO) system by employing two technologies which improve the performance of neural network in deep physics-info…

nlin.PS2021★ 89 cited

Data-driven vector localized waves and parameters discovery for Manakov system using deep learning approach

Juncai Pu, Yong Chen

An improved physics-informed neural network (IPINN) algorithm with four output functions and four physics constraints, which possesses neuron-wise locally adaptive activation funct…

nlin.SI2021

The data-driven localized wave solutions of the derivative nonlinear Schrodinger equation by using improved PINN approach

Juncai Pu, Weiqi Peng, Yong Chen

The research of the derivative nonlinear Schrodinger equation (DNLS) has attracted more and more extensive attention in theoretical analysis and physical application. The improved…

nlin.SI2021★ 131 cited

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

Weiqi Peng, Juncai Pu, Yong Chen

We consider the exact rogue periodic wave (rogue wave on the periodic background) and periodic wave solutions for the Chen-Lee-Liu equation via the odd-th order Darboux transformat…

nlin.SI2021★ 1 cited

Double and Triple-Pole Solutions for the Third-Order Flow Equation of the Kaup-Newell System with Zero/Nonzero Boundary Conditions

Juncai Pu, Yong Chen

In this work, the double and triple-pole solutions for the third-order flow equation of Kaup-Newell system (TOFKN) with zero boundary conditions (ZBCs) and non-zero boundary condit…

nlin.PS2021★ 3 cited

Solving localized wave solutions of the derivative nonlinear Schrodinger equation using an improved PINN method

Juncai Pu, Jun Li, Yong Chen

The solving of the derivative nonlinear Schrodinger equation (DNLS) has attracted considerable attention in theoretical analysis and physical applications. Based on the physics-inf…

nlin.SI2020★ 3 cited

Soliton, Breather and Rogue Wave Solutions for Solving the Nonlinear Schrödinger Equation Using a Deep Learning Method with Physical Constraints

Juncai Pu, Jun Li, Yong Chen

The nonlinear Schrodinger equation is a classical integrable equation which contains plenty of significant properties and occurs in many physical areas. However, due to the difficu…