Incremental learning model for dynamical identification and classification of abnormal vibration in operational underground facilities-Reference-Cited by-同舟云学术

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Incremental learning model for dynamical identification and classification of abnormal vibration in operational underground facilities

Published:2023-10 Issue: Volume:140 Page:105251
ISSN:0886-7798
Container-title:Tunnelling and Underground Space Technology
language:en
Short-container-title:Tunnelling and Underground Space Technology

Author:

Chai Fu,Zhou Biao,Xie Xiongyao,Zhang Zixin,Wang Chen

Funder

State Grid Shanghai Municipal Electric Power Company

Science and Technology Innovation Plan Of Shanghai Science and Technology Commission

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Building and Construction

Reference38 articles.

1. Risk-cost optimised maintenance strategy for tunnel structures;Baji;J. Tunn. Undergr. Sp. Tech.,2017

2. Representation learning: a review and new perspectives;Bengio;Proc. IEEE Trans. Pattern Anal. Mach. Intell.,2013

3. Structural damage detection based on variational mode decomposition and kernel PCA-based support vector machine;Bisheh;J. Eng. Struct.,2023

4. Modal-parameter identification and vibration-based damage detection of a damaged steel truss bridge;Chang;J. Eng. Struct.,2016

5. Incremental supervised learning: algorithms and application in pattern recognition;Chefrour;J. Evol. Intell.,2019

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2. Multi-sample joint localization method for intrusion sources around underground pipelines based on cross-correlation convolutional neural networks;IOP Conference Series: Earth and Environmental Science;2024-05-01

3. An intelligent construction model in whole process for shield tunnelling;2024-04-25

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