CNN-DP: composite neural network with differential propagation for impulsive nonlinear dynamics

DOI10.1016/j.jcp.2023.112578MaRDI QIDQ6202143

Hyeonbeen Lee, Jin-Gyun Kim, Hee-Sun Choi, Seongji Han

Publication date: 21 February 2024

Published in: Journal of Computational Physics (Search for Journal in Brave)

zbMATH Keywords

nonlinear dynamicssurrogate modelingimpulsive dynamicsdata-driven modelingcomposite neural network

Mathematics Subject Classification ID

Numerical approximation and computational geometry (primarily algorithms) (65Dxx) Artificial intelligence (68Txx) Numerical methods for ordinary differential equations (65Lxx)

Cites Work

• Unnamed Item
• Chaos in the fractional-order complex Lorenz system and its synchronization
• A DNN-based data-driven modeling employing coarse sample data for real-time flexible multibody dynamics simulations
• Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization
• Data-driven simulation for general-purpose multibody dynamics using deep neural networks
• Multi-fidelity meta modeling using composite neural network with online adaptive basis technique
• DeepM\&Mnet: inferring the electroconvection multiphysics fields based on operator approximation by neural networks
• When and why PINNs fail to train: a neural tangent kernel perspective
• Conservative physics-informed neural networks on discrete domains for conservation laws: applications to forward and inverse problems
• A composite neural network that learns from multi-fidelity data: application to function approximation and inverse PDE problems
• Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
• Large Sample Properties of Simulations Using Latin Hypercube Sampling
• Deterministic Nonperiodic Flow
• Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations
• Deep learning in fluid dynamics
• A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures
• A Stochastic Approximation Method

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