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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Recurrent neural network model with Bayesian training and mutual information for response prediction of large buildings
Carlos A. Perez-Ramirez, Juan P. Amézquita-Sánchez, Martin Valtierra‐Rodriguez, et al.
Engineering Structures (2018) Vol. 178, pp. 603-615
Closed Access | Times Cited: 212

Showing 1-25 of 212 citing articles:

Roles of artificial intelligence in construction engineering and management: A critical review and future trends
Yue Pan, Limao Zhang
Automation in Construction (2020) Vol. 122, pp. 103517-103517
Closed Access | Times Cited: 741
Concrete crack detection using context‐aware deep semantic segmentation network
Xinxiang Zhang, Dinesh Rajan, Brett Story
Computer-Aided Civil and Infrastructure Engineering (2019) Vol. 34, Iss. 11, pp. 951-971
Closed Access | Times Cited: 167
Real‐time regional seismic damage assessment framework based on long short‐term memory neural network
Yongjia Xu, Xinzheng Lu, Barbaros Çetiner, et al.
Computer-Aided Civil and Infrastructure Engineering (2020) Vol. 36, Iss. 4, pp. 504-521
Closed Access | Times Cited: 137
State-of-the-art review on advancements of data mining in structural health monitoring
Meisam Gordan, Saeed-Reza Sabbagh-Yazdi, Zubaidah Ismail, et al.
Measurement (2022) Vol. 193, pp. 110939-110939
Closed Access | Times Cited: 126
Seismic control of adaptive variable stiffness intelligent structures using fuzzy control strategy combined with LSTM
Han Zhang, Liangkun Wang, Weixing Shi
Journal of Building Engineering (2023) Vol. 78, pp. 107549-107549
Closed Access | Times Cited: 81
Transformer‐optimized generation, detection, and tracking network for images with drainage pipeline defects
Duo Ma, Hongyuan Fang, Niannian Wang, et al.
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 38, Iss. 15, pp. 2109-2127
Closed Access | Times Cited: 53
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics
Salah A. Faroughi, Nikhil M. Pawar, Célio Fernandes, et al.
Journal of Computing and Information Science in Engineering (2024) Vol. 24, Iss. 4
Closed Access | Times Cited: 41
LSTM, WaveNet, and 2D CNN for nonlinear time history prediction of seismic responses
Chunxiao Ning, Yazhou Xie, Lijun Sun
Engineering Structures (2023) Vol. 286, pp. 116083-116083
Closed Access | Times Cited: 40
Advances in artificial intelligence for structural health monitoring: A comprehensive review
Billie F. Spencer, Sung‐Han Sim, Robin E. Kim, et al.
KSCE Journal of Civil Engineering (2025) Vol. 29, Iss. 3, pp. 100203-100203
Open Access | Times Cited: 1
Noncontact cable force estimation with unmanned aerial vehicle and computer vision
Yongding Tian, Cheng Zhang, Shang Jiang, et al.
Computer-Aided Civil and Infrastructure Engineering (2020) Vol. 36, Iss. 1, pp. 73-88
Closed Access | Times Cited: 134
Empirical mode decomposition and its variants: a review with applications in structural health monitoring
Mohamed Barbosh, Premjeet Singh, Ayan Sadhu
Smart Materials and Structures (2020) Vol. 29, Iss. 9, pp. 093001-093001
Closed Access | Times Cited: 131
A deep learning‐based image captioning method to automatically generate comprehensive explanations of bridge damage
Pang-jo CHUN, Tatsuro Yamane, Yu Maemura
Computer-Aided Civil and Infrastructure Engineering (2021) Vol. 37, Iss. 11, pp. 1387-1401
Open Access | Times Cited: 94
Seismic response prediction method for building structures using convolutional neural network
Byung Kwan Oh, Young‐Jun Park, Hyo Seon Park
Structural Control and Health Monitoring (2020) Vol. 27, Iss. 5
Open Access | Times Cited: 92
Convolutional neural network–based data recovery method for structural health monitoring
Byung Kwan Oh, Branko Glišić, Yousok Kim, et al.
Structural Health Monitoring (2020) Vol. 19, Iss. 6, pp. 1821-1838
Closed Access | Times Cited: 87
Automatic railroad track components inspection using real‐time instance segmentation
Feng Guo, Yu Qian, Yunpeng Wu, et al.
Computer-Aided Civil and Infrastructure Engineering (2020) Vol. 36, Iss. 3, pp. 362-377
Closed Access | Times Cited: 87
Applicability of machine learning to a crack model in concrete bridges
Yuriko Okazaki, Shinichiro Okazaki, Shingo Asamoto, et al.
Computer-Aided Civil and Infrastructure Engineering (2020) Vol. 35, Iss. 8, pp. 775-792
Closed Access | Times Cited: 84
Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring
Huachen Jiang, Chunfeng Wan, Kang Yang, et al.
Structural Health Monitoring (2021) Vol. 21, Iss. 3, pp. 1093-1109
Closed Access | Times Cited: 76
Balanced semisupervised generative adversarial network for damage assessment from low‐data imbalanced‐class regime
Yuqing Gao, Pengyuan Zhai, Khalid M. Mosalam
Computer-Aided Civil and Infrastructure Engineering (2021) Vol. 36, Iss. 9, pp. 1094-1113
Open Access | Times Cited: 75
Vibration-based multiclass damage detection and localization using long short-term memory networks
Sandeep Sony, Sunanda Gamage, Ayan Sadhu, et al.
Structures (2021) Vol. 35, pp. 436-451
Closed Access | Times Cited: 73
Bayesian‐optimized unsupervised learning approach for structural damage detection
Kareem Eltouny, Xiao Liang
Computer-Aided Civil and Infrastructure Engineering (2021) Vol. 36, Iss. 10, pp. 1249-1269
Closed Access | Times Cited: 64
Multicategory damage detection and safety assessment of post‐earthquake reinforced concrete structures using deep learning
Dujian Zou, Ming Zhang, Zhilin Bai, et al.
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 37, Iss. 9, pp. 1188-1204
Closed Access | Times Cited: 60
A Bayesian deep learning approach for random vibration analysis of bridges subjected to vehicle dynamic interaction
Huile Li, Tianyu Wang, Gang Wu
Mechanical Systems and Signal Processing (2022) Vol. 170, pp. 108799-108799
Closed Access | Times Cited: 59
Large‐scale structural health monitoring using composite recurrent neural networks and grid environments
Kareem Eltouny, Xiao Liang
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 38, Iss. 3, pp. 271-287
Closed Access | Times Cited: 57
Multifidelity approach for data‐driven prediction models of structural behaviors with limited data
Shi‐Zhi Chen, De‐Cheng Feng
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 37, Iss. 12, pp. 1566-1581
Closed Access | Times Cited: 48
Toward a general unsupervised novelty detection framework in structural health monitoring
Mohammad Hesam Soleimani‐Babakamali, Reza Sepasdar, Kourosh Nasrollahzadeh, et al.
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 37, Iss. 9, pp. 1128-1145
Closed Access | Times Cited: 45
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