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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:

Efficient Artificial neural networks based on a hybrid metaheuristic optimization algorithm for damage detection in laminated composite structures
H. Tran-Ngoc, Samir Khatir, H. Ho-Khac, et al.
Composite Structures (2020) Vol. 262, pp. 113339-113339
Closed Access | Times Cited: 116

Showing 1-25 of 116 citing articles:

Structural Health Monitoring in Composite Structures: A Comprehensive Review
Sahar Hassani, Mohsen Mousavi, Amir H. Gandomi
Sensors (2021) Vol. 22, Iss. 1, pp. 153-153
Open Access | Times Cited: 134
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: 129
A Systematic Review of Optimization Algorithms for Structural Health Monitoring and Optimal Sensor Placement
Sahar Hassani, Ulrike Dackermann
Sensors (2023) Vol. 23, Iss. 6, pp. 3293-3293
Open Access | Times Cited: 60
A review on recent developments in vibration-based damage identification methods for laminated composite structures: 2010–2022
Pankaj Chaupal, Prakash Rajendran
Composite Structures (2023) Vol. 311, pp. 116809-116809
Closed Access | Times Cited: 56
Structure damage identification in dams using sparse polynomial chaos expansion combined with hybrid K-means clustering optimizer and genetic algorithm
Yifei Li, Hoang-Le Minh, Samir Khatir, et al.
Engineering Structures (2023) Vol. 283, pp. 115891-115891
Closed Access | Times Cited: 55
Artificial-intelligence-led revolution of construction materials: From molecules to Industry 4.0
Xing Quan Wang, Pengguang Chen, Cheuk Lun Chow, et al.
Matter (2023) Vol. 6, Iss. 6, pp. 1831-1859
Open Access | Times Cited: 52
An integrated surrogate model-driven and improved termite life cycle optimizer for damage identification in dams
Yifei Li, Hoang-Le Minh, Maosen Cao, et al.
Mechanical Systems and Signal Processing (2023) Vol. 208, pp. 110986-110986
Open Access | Times Cited: 49
Damage detection on rectangular laminated composite plates using wavelet based convolutional neural network technique
Morteza Saadatmorad, Ramazan‐Ali Jafari‐Talookolaei, Mohammad-Hadi Pashaei, et al.
Composite Structures (2021) Vol. 278, pp. 114656-114656
Closed Access | Times Cited: 61
Intelligent fault diagnosis and visual interpretability of rotating machinery based on residual neural network
Shihang Yu, Min Wang, Shanchen Pang, et al.
Measurement (2022) Vol. 196, pp. 111228-111228
Closed Access | Times Cited: 57
Damage assessment in laminated composite plates using modal Strain Energy and YUKI-ANN algorithm
Muhammad Irfan Shirazi, Samir Khatir, Brahim Benaissa, et al.
Composite Structures (2022) Vol. 303, pp. 116272-116272
Open Access | Times Cited: 54
Automated identification of compressive stress and damage in concrete specimen using convolutional neural network learned electromechanical admittance
Demi Ai, Fang Mo, Yihang Han, et al.
Engineering Structures (2022) Vol. 259, pp. 114176-114176
Closed Access | Times Cited: 50
Intelligent structural health monitoring of composite structures using machine learning, deep learning, and transfer learning: a review
Muhammad Muzammil Azad, Sungjun Kim, Yu Bin Cheon, et al.
Advanced Composite Materials (2023) Vol. 33, Iss. 2, pp. 162-188
Closed Access | Times Cited: 40
Random forest-based surrogates for transforming the behavioral predictions of laminated composite plates and shells from FSDT to Elasticity solutions
Aman Garg, T. Mukhopadhyay, Mohamed‐Ouejdi Belarbi, et al.
Composite Structures (2023) Vol. 309, pp. 116756-116756
Closed Access | Times Cited: 30
A novel dynamic opposite learning enhanced Jaya optimization method for high efficiency plate–fin heat exchanger design optimization
Lidong Zhang, Tianyu Hu, Linxin Zhang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 119, pp. 105778-105778
Open Access | Times Cited: 30
Physics-guided deep learning for damage detection in CFRP composite structures
Xuebing Xu, Cheng Liu
Composite Structures (2024) Vol. 331, pp. 117889-117889
Closed Access | Times Cited: 14
Forecasting and characterization of composite pipeline based on experimental modal analysis and YUKI-gradient boosting
Meriem Seguini, Samir Khatir, Djilali Boutchicha, et al.
Construction and Building Materials (2024) Vol. 425, pp. 135625-135625
Closed Access | Times Cited: 9
A methodology for sensor number and placement optimization for vibration-based damage detection of composite structures under model uncertainty
Haichao An, Byeng D. Youn, Heung Soo Kim
Composite Structures (2021) Vol. 279, pp. 114863-114863
Closed Access | Times Cited: 46
Finite element model updating of a multispan bridge with a hybrid metaheuristic search algorithm using experimental data from wireless triaxial sensors
H. Tran-Ngoc, Samir Khatir, T. Le-Xuan, et al.
Engineering With Computers (2021) Vol. 38, Iss. S3, pp. 1865-1883
Closed Access | Times Cited: 45
Artificial neural network combined with damage parameters to predict fretting fatigue crack initiation lifetime
Can Wang, Yifei Li, Ngoc Hoa Tran, et al.
Tribology International (2022) Vol. 175, pp. 107854-107854
Closed Access | Times Cited: 36
A novel version of grey wolf optimizer based on a balance function and its application for hyperparameters optimization in deep neural network (DNN) for structural damage identification
Thanh Cuong‐Le, Hoang-Le Minh, Thanh Sang-To, et al.
Engineering Failure Analysis (2022) Vol. 142, pp. 106829-106829
Open Access | Times Cited: 29
On the Use of Machine Learning for Damage Assessment in Composite Structures: A Review
Ronny Francis Ribeiro, Guilherme Ferreira Gomes
Applied Composite Materials (2023) Vol. 31, Iss. 1, pp. 1-37
Closed Access | Times Cited: 17
Deep long short-term memory neural network for accelerated elastoplastic analysis of heterogeneous materials: An integrated data-driven surrogate approach
Qiang Chen, Ruijian Jia, Shanmin Pang
Composite Structures (2021) Vol. 264, pp. 113688-113688
Closed Access | Times Cited: 41
Developing the artificial neural network–evolutionary algorithms hybrid models (ANN–EA) to predict the daily evaporation from dam reservoirs
Naser Arya Azar, Nazila Kardan, Sami Ghordoyee Milan
Engineering With Computers (2021) Vol. 39, Iss. 2, pp. 1375-1393
Closed Access | Times Cited: 41
Real-time prediction of the mechanical behavior of suction caisson during installation process using GA-BP neural network
Shengshen Wu, Gao‐Feng Zhao, Bisheng Wu
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105475-105475
Closed Access | Times Cited: 27
A self-learning hyper-heuristic for the distributed assembly blocking flow shop scheduling problem with total flowtime criterion
Fuqing Zhao, Shilu Di, Ling Wang, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105418-105418
Closed Access | Times Cited: 24
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