Zero-shot knowledge transfer for seismic damage diagnosis through multi-channel 1D CNN integrated with autoencoder-based domain adaptation-Reference-Cited by-同舟云学术

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Zero-shot knowledge transfer for seismic damage diagnosis through multi-channel 1D CNN integrated with autoencoder-based domain adaptation

Published:2024-08 Issue: Volume:217 Page:111535
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Xiong Qingsong,Kong Qingzhao,Xiong Haibei,Chen Jiawei,Yuan Cheng,Wang Xiaoyou,Xia Yong^ORCID

Publisher

Elsevier BV

Reference57 articles.

1. Monitoring seismic damage via accelerometer data alone using Volterra series and genetic algorithm;Alexander;Mech. Syst. Sig. Process.,2023

2. Real-time regional seismic damage assessment framework based on long short-term memory neural network;Xu;Comput. Aided Civ. Inf. Eng.,2020

3. Automated real-time damage detection strategy using raw dynamic measurements;de Almeida;Eng. Struct.,2019

4. A review of the research and application of deep learning-based computer vision in structural damage detection;Lingxin;Earthq. Eng. Eng. Vib.,2022

5. Seismic fragility analysis of bridges by relevance vector machine based demand prediction model;Ghosh;Earthq. Eng. Eng. Vib.,2022

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