A review of machine learning methods applied to structural dynamics and vibroacoustic-Reference-Cited by-同舟云学术

A review of machine learning methods applied to structural dynamics and vibroacoustic

Published:2023-10 Issue: Volume:200 Page:110535
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Zaparoli Cunha Barbara,Droz Christophe,Zine Abdel-Malek^ORCID,Foulard Stéphane,Ichchou Mohamed

Funder

H2020 Marie Skłodowska-Curie Actions

Horizon 2020

Horizon 2020 Framework Programme

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference477 articles.

1. Digital technology and social change: The digital transformation of society from a historical perspective;Hilbert;Dialogues Clin. Neurosci.,2020

2. Artificial intelligence in healthcare;Yu;Nat. Biomed. Eng.,2018

3. Autonomous vehicles: State of the art, future trends, and challenges;Mallozzi;Automot. Syst. Softw. Eng.,2019

4. Forecasting inflation in a data-rich environment: The benefits of machine learning methods;Medeiros;J. Bus. Econom. Statist.,2021

5. Detecting fake news using machine learning: A systematic literature review;Ahmed,2021

Cited by 37 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel LSTM-integrated non-intrusive ROM for reliability analysis of hysteretic systems with large stochastic dimension;International Journal of Non-Linear Mechanics;2024-10

2. Enhancing the maintenance strategy and cost in systems with surrogate assisted multiobjective evolutionary algorithms;Developments in the Built Environment;2024-10

3. Machine learning and numerical approaches for vibration behavior prediction of rotating nanobeams in complex environments;Mechanics of Advanced Materials and Structures;2024-09-09

4. Damage Detection and Localization Methodology Based on Strain Measurements and Finite Element Analysis: Structural Health Monitoring in the Context of Industry 4.0;Aerospace;2024-08-30

5. Extrapolation of Physics-Inspired Deep Networks in Learning Robot Inverse Dynamics;Mathematics;2024-08-15