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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:

Convolutional neural network‐based wind‐induced response estimation model for tall buildings
Byung Kwan Oh, Branko Glišić, Yousok Kim, et al.
Computer-Aided Civil and Infrastructure Engineering (2019) Vol. 34, Iss. 10, pp. 843-858
Open Access | Times Cited: 99

Showing 26-50 of 99 citing articles:

Machine Learning Techniques in Structural Wind Engineering: A State-of-the-Art Review
Karim Mostafa, Ioannis Zisis, Mohamed A. Moustafa
Applied Sciences (2022) Vol. 12, Iss. 10, pp. 5232-5232
Open Access | Times Cited: 25
Explainable machine learning-based prediction for aerodynamic interference of a low-rise building on a high-rise building
Bowen Yan, Wenhao Ding, Zhao Jin, et al.
Journal of Building Engineering (2023) Vol. 82, pp. 108285-108285
Closed Access | Times Cited: 14
DNN surrogate model based cable force optimization for cantilever erection construction of large span arch bridge with concrete filled steel tube
Xiaohang Zhou, Lu Cao, Weiwei Xie, et al.
Advances in Engineering Software (2024) Vol. 189, pp. 103588-103588
Closed Access | Times Cited: 4
Convolutional neural network-based wind pressure prediction on low-rise buildings
Youqin Huang, Huifan Wu, Jiyang Fu, et al.
Engineering Structures (2024) Vol. 309, pp. 118078-118078
Closed Access | Times Cited: 4
Deep Learning-Based Imputation Framework for Bridge Health Monitoring using Generative Adversarial Networks
Sumit Saha, Krishn Katyal, S. Somala
Knowledge-Based Systems (2025), pp. 113088-113088
Closed Access
A survey on machine learning approaches for uncertainty quantification of engineering systems
Yan Shi, Pengfei Wei, Ke Feng, et al.
Machine learning for computational science and engineering (2025) Vol. 1, Iss. 1
Open Access
Machine learning-based strain response prediction method for structural members of a building using ground motion data and intensity measures
Hyo Park, Byung Kwan Oh
Advances in Structural Engineering (2025)
Closed Access
Intelligent long-term prediction of wind-induced response of super high-rise buildings during typhoons based on wind tunnel tests
Feiqiang Li, Zhuangning Xie, Lanfang Zhang, et al.
Journal of Building Engineering (2025), pp. 112144-112144
Closed Access
Data-driven wind-induced response prediction for slender civil infrastructure: Progress, challenges and opportunities
Yiming Zhang, Haoqing Li, Hao Wang
Structures (2025) Vol. 74, pp. 108650-108650
Closed Access
Recovery of Long-Term Missing Wind Velocity Data for Structural Health Monitoring Based on Deep Learning and Meteorological Databases
Jia-Xing Huang, Q.S. Li, Xu‐Liang Han, et al.
Journal of Structural Engineering (2025) Vol. 151, Iss. 6
Closed Access
Deep Learning Based Vehicle Detection and Classification Methodology Using Strain Sensors under Bridge Deck
Rujin Ma, Zhen Zhang, Yiqing Dong, et al.
Sensors (2020) Vol. 20, Iss. 18, pp. 5051-5051
Open Access | Times Cited: 37
A Gaussian Process-Based emulator for modeling pedestrian-level wind field
A.U. Weerasuriya, Xuelin Zhang, Bin Lu, et al.
Building and Environment (2020) Vol. 188, pp. 107500-107500
Open Access | Times Cited: 32
Bibliometric analysis and critical review of the research on big data in the construction industry
Yusheng Lu, Jiantong Zhang
Engineering Construction & Architectural Management (2021) Vol. 29, Iss. 9, pp. 3574-3592
Closed Access | Times Cited: 28
Artificial intelligence in civil infrastructure health monitoring—Historical perspectives, current trends, and future visions
Tarutal Ghosh Mondal, Genda Chen
Frontiers in Built Environment (2022) Vol. 8
Open Access | Times Cited: 20
Deep learning based missing data recovery of non-stationary wind velocity
Qiushuang Lin, Xuming Bao, Chunxiang Li
Journal of Wind Engineering and Industrial Aerodynamics (2022) Vol. 224, pp. 104962-104962
Closed Access | Times Cited: 19
Deep Learning Models for Time-History Prediction of Vehicle-Induced Bridge Responses: A Comparative Study
Huile Li, Tianyu Wang, Judy P. Yang, et al.
International Journal of Structural Stability and Dynamics (2022) Vol. 23, Iss. 01
Closed Access | Times Cited: 19
Wind loads on buildings: A code of practice perspective
Ted Stathopoulos, Hatem Alrawashdeh
Journal of Wind Engineering and Industrial Aerodynamics (2020) Vol. 206, pp. 104338-104338
Open Access | Times Cited: 29
Optimal architecture of a convolutional neural network to estimate structural responses for safety evaluation of the structures
Byung Kwan Oh, Jimin Kim
Measurement (2021) Vol. 177, pp. 109313-109313
Closed Access | Times Cited: 26
Active learning method for risk assessment of distributed infrastructure systems
Agam Tomar, Henry Burton
Computer-Aided Civil and Infrastructure Engineering (2021) Vol. 36, Iss. 4, pp. 438-452
Closed Access | Times Cited: 24
Motor Intention Decoding from the Upper Limb by Graph Convolutional Network Based on Functional Connectivity
Naishi Feng, Fo Hu, Hong Wang, et al.
International Journal of Neural Systems (2021) Vol. 31, Iss. 12
Closed Access | Times Cited: 23
Hybrid random aggregation model and Bayesian optimization‐based convolutional neural network for estimating the concrete compressive strength
Kai Li, Lei Pan, Xiaohui Guo, et al.
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 4, pp. 559-574
Open Access | Times Cited: 10
The Short-Term Prediction of Wind Power Based on the Convolutional Graph Attention Deep Neural Network
Fan Xiao, Xiong Ping, Y. Li, et al.
Energy Engineering (2024) Vol. 121, Iss. 2, pp. 359-376
Open Access | Times Cited: 3
Deep recurrent-convolutional neural network learning and physics Kalman filtering comparison in dynamic load identification
Marios Impraimakis
Structural Health Monitoring (2024)
Open Access | Times Cited: 3
Comparative study on deep and machine learning approaches for predicting wind pressures on tall buildings
Mosbeh R. Kaloop, Abidhan Bardhan, Pijush Samui, et al.
Alexandria Engineering Journal (2024) Vol. 111, pp. 610-627
Closed Access | Times Cited: 3
Wind-Induced Pressure Prediction on Tall Buildings Using Generative Adversarial Imputation Network
Bubryur Kim, N. Yuvaraj, K. R. Sri Preethaa, et al.
Sensors (2021) Vol. 21, Iss. 7, pp. 2515-2515
Open Access | Times Cited: 22

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