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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:

A rapid machine learning-based damage detection algorithm for identifying the extent of damage in concrete shear-wall buildings
Hossein Mahmoudi, Maryam Bitaraf, Mojtaba Salkhordeh, et al.
Structures (2022) Vol. 47, pp. 482-499
Closed Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Ensemble machine learning-based approach with genetic algorithm optimization for predicting bond strength and failure mode in concrete-GFRP mat anchorage interface
Alireza Mahmoudian, Nima Tajik, Mostafa Mohammadzadeh Taleshi, et al.
Structures (2023) Vol. 57, pp. 105173-105173
Closed Access | Times Cited: 28
Damage detection of structures based on wavelet analysis using improved AlexNet
Hessam Amanollah, Arghavan Asghari, ‪Mohammadreza Mashayekhi, et al.
Structures (2023) Vol. 56, pp. 105019-105019
Closed Access | Times Cited: 22
Mechanism-driven and data-driven fusion prediction of seismic damage evolution of concrete structures based on cooperative multi-particle swarm optimization
Bin Sun, Tong Guo
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108659-108659
Closed Access | Times Cited: 9
Damage detection in power transmission towers using machine learning algorithms
Mehdi Kouchaki, Mojtaba Salkhordeh, ‪Mohammadreza Mashayekhi, et al.
Structures (2023) Vol. 56, pp. 104980-104980
Closed Access | Times Cited: 17
A Rapid Machine Learning-Based Damage Detection Technique for Detecting Local Damages in Reinforced Concrete Bridges
Mojtaba Salkhordeh, Masoud Mirtaheri, Najib Rabiee, et al.
Journal of Earthquake Engineering (2023) Vol. 27, Iss. 16, pp. 4705-4738
Closed Access | Times Cited: 16
Advanced tree-based machine learning methods for predicting the seismic response of regular and irregular RC frames
Ahmet Demir, Emrehan Kutluğ Şahin, Selçuk Demir
Structures (2024) Vol. 64, pp. 106524-106524
Closed Access | Times Cited: 7
Dynamic constitutive identification of concrete based on improved dung beetle algorithm to optimize long short-term memory model
Ping Li, Haonan Zhao, Jiming Gu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Damage Detection and Localization in Sealed Spent Nuclear Fuel Dry Storage Canisters using Multi-task Machine Learning Classifiers
Anna Arcaro, Bozhou Zhuang, Bora Gencturk, et al.
Reliability Engineering & System Safety (2024) Vol. 252, pp. 110446-110446
Open Access | Times Cited: 4
Performance of precast short-leg concrete shear walls with insufficient splicing bar anchorage
Liwei Li, Qian Huang, Tan Wang, et al.
Structures (2025) Vol. 72, pp. 108235-108235
Closed 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
Encoder-based attention mechanism deep learning network for clip damage detection in metal roofing systems
Li Zou, Jun Hu, Heung‐Fai Lam, et al.
Structural Health Monitoring (2025)
Closed Access
Damage detection and noise cancelation algorithm in building structures using autocorrelation data and improved pattern construction method
Panam Zarfam, Fatemeh A. Mehrabadi, Armin Aziminejad
Structural Health Monitoring (2025)
Closed Access
The hybrid “M and P” technique for seismic damage identification in planar dual reinforced concrete frames
Triantafyllos K. Makarios, Athanasios P. Bakalis, Ioannis Ntaliakouras, et al.
Soil Dynamics and Earthquake Engineering (2025) Vol. 194, pp. 109344-109344
Open Access
A review of non-destructive testing techniques for shear wall structures with modular integrated construction
Jiang Wang, Va Kong, Xiuquan Li, et al.
Journal of Building Engineering (2025), pp. 112337-112337
Closed Access
InCR: Inception and concatenation residual block-based deep learning network for damaged building detection using remote sensing images
Burak Taşçı, Madhav R. Acharya, Mehmet Bayğın, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 123, pp. 103483-103483
Open Access | Times Cited: 9
Automated operational modal analysis for supertall buildings based on a three-stage strategy and modified hierarchical clustering
Kun Zhao, Q.S. Li, Mengmeng Sun, et al.
Structures (2024) Vol. 62, pp. 106194-106194
Closed Access | Times Cited: 3
Infrastructure damage assessment via machine learning approaches: a systematic review
Mohammadmahdi Abedi, Javad Shayanfar, Khalifa Al‐Jabri
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 8, pp. 3823-3852
Closed Access | Times Cited: 7
Vibration-based structural damage detection strategy using FRFs and machine learning classifiers
Dianelys Vega Ruiz, Cássio Bragança, Bernardo Lopes Poncetti, et al.
Structures (2023) Vol. 59, pp. 105753-105753
Closed Access | Times Cited: 7
Investigation on employment of time and frequency domain data for predicting nonlinear seismic responses of structures
Hyo Seon Park, Sang Hoon Yoo, Da Yo Yun, et al.
Structures (2024) Vol. 61, pp. 105996-105996
Open Access | Times Cited: 2
A robust approach for bond strength prediction of mortar using machine learning with SHAP interpretability
Kai Wu, Sihao Zhou, Qiang Li, et al.
Materials Today Communications (2024), pp. 110667-110667
Closed Access | Times Cited: 2
Assessment of geometric parameters of segmented crack on concrete building facade using deep learning
Shan Xu, H L Tang, Xinran Wang, et al.
Structures (2023) Vol. 57, pp. 105188-105188
Closed Access | Times Cited: 5
Prediction of frost resistance and multiobjective optimisation of low-carbon concrete on the basis of machine learning
Jinpeng Dai, Zhijie Zhang, Xuwei Dong, et al.
Materials Today Communications (2024) Vol. 40, pp. 109525-109525
Closed Access | Times Cited: 1
A boosted deep learning-based approach for near real-time response estimation of structures under ground motion excitations
Mohammad Javad Kaffashchian, Mojtaba Salkhordeh, Reza Karami Mohammadi
Structure and Infrastructure Engineering (2024), pp. 1-20
Closed Access | Times Cited: 1
A stacking learning-based method for identifying the structural damage in structures
Ehsan Madani, Alireza Fiouz, Davood Abdollahzadeh, et al.
Structures (2024) Vol. 70, pp. 107864-107864
Closed Access | Times Cited: 1
Rapid Seismic Damage Assessment of RC Bridges Considering Time–Frequency Characteristics of Ground Motions
Lang Liu, Siyu Miao, Yumin Song, et al.
Iranian Journal of Science and Technology Transactions of Civil Engineering (2024)
Closed Access
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