Structural Damage Identification System Suitable for Old Arch Bridge in Rural Regions: Random Forest Approach-Reference-Cited by-同舟云学术

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Structural Damage Identification System Suitable for Old Arch Bridge in Rural Regions: Random Forest Approach

Published:2023 Issue:1 Volume:136 Page:447-469
ISSN:1526-1506
Container-title:Computer Modeling in Engineering & Sciences
language:en
Short-container-title:

Author:

Zhang Yu,Xiong Zhihua,Liang Zhuoxi,She Jiachen,Ma Chicheng

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Computer Science Applications,Modeling and Simulation,Software

Link

https://www.techscience.com/CMES/v136n1/51182/pdf

Reference38 articles.

1. Construction of rapid evaluation system of old stone arch bridge in Shaanxi Province;Zhang;Journal of Water Resources and Architectural Engineering,2021

2. Ultimate bending strength evaluation of MVFT composite girder by using finite element method and machine learning regressors;Xiong;Latin American Journal of Solids and Structures,2022

3. A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications;Avci;Mechanical Systems and Signal Processing,2021

4. Rapid seismic damage evaluation of bridge portfolios using machine learning techniques;Mangalathu,2019

5. Machine learning technologies for big data analytics;Gandomi;Electronics,2022

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3. An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate;Computer Modeling in Engineering & Sciences;2024

4. Structural Modal Calibration of Historical Masonry Arch Bridge by Using a Novel Deep Neural Network Approach;Iranian Journal of Science and Technology, Transactions of Civil Engineering;2023-12-12

5. Operational Modal Analysis on Bridges: A Comprehensive Review;Infrastructures;2023-12-04

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