Deep neural network method to predict the dynamical system response under random excitation of combined Gaussian and Poisson white noises-Reference-Cited by-同舟云学术

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Deep neural network method to predict the dynamical system response under random excitation of combined Gaussian and Poisson white noises

Published:2024-08 Issue: Volume:185 Page:115134
ISSN:0960-0779
Container-title:Chaos, Solitons & Fractals
language:en
Short-container-title:Chaos, Solitons & Fractals

Author:

Jia Wantao^ORCID,Feng Xiaotong,Hao Mengli,Ma Shichao

Publisher

Elsevier BV

Reference40 articles.

1. Stochastic modeling of nonlinear oscillators under combined Gaussian and Poisson white noise: a viewpoint based on the energy conservation law;Sun;Nonlinear Dynam,2016

2. Stochastic stability of quasi-integrable and non-resonant Hamiltonian systems under parametric excitations of combined Gaussian and Poisson white noises;Liu;Int J Nonlin Mech,2014

3. A theoretical analysis for mean exit time of a Bi-stable system under combined Gaussian and Poisson white noise excitations;Guo;Optik,2017

4. Path integral methods for the probabilistic analysis of nonlinear systems under a white-noise process;Di Paola;Asce-Asme J Risk U B,2020

5. Reliability of dynamical systems with combined Gaussian and Poisson white noise via path integral method;Zan;Probabilistic Eng Mech,2022

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