Experimental validation of a deep neural network-Sparse representation classification ensemble method
Author:
Affiliation:
1. Faculty of Civil Engineering; Amirkabir University of Technology; Tehran Iran
2. Central Tehran Branch; Islamic Azad University; Tehran Iran
3. Faculty of Mechanical Engineering; Universidad de Chile; Beauchef 850 Santiago Chile
Publisher
Wiley
Subject
Building and Construction,Architecture,Civil and Structural Engineering
Link
http://onlinelibrary.wiley.com/wol1/doi/10.1002/tal.1504/fullpdf
Reference37 articles.
1. Structural damage diagnosis using modal data
2. DAMAGE DETECTION USING THE FREQUENCY-RESPONSE-FUNCTION CURVATURE METHOD
3. CATEGORISATION AND PATTERN RECOGNITION METHODS FOR DAMAGE LOCALISATION FROM VIBRATION MEASUREMENTS
Cited by 14 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. Structural damage quantification using long short-term memory (LSTM) auto-encoder and impulse response functions;Journal of Infrastructure Intelligence and Resilience;2024-06
2. Online electronic signature recognition using sparse classification techniques that support neural models;Journal of Computational Methods in Sciences and Engineering;2024-03-14
3. Towards vibration-based damage detection of civil engineering structures: overview, challenges, and future prospects;International Journal of Mechanics and Materials in Design;2024-01-08
4. A novel multi-fidelity neural network for response prediction using rotor dynamics and model reduction;Journal of the Brazilian Society of Mechanical Sciences and Engineering;2023-10-25
5. Bridge damage analysis under joint environmental and operational variability;Structure and Infrastructure Engineering;2023-08-04
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3