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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:

Multiaxial fatigue life prediction for various metallic materials based on the hybrid CNN‐LSTM neural network
Fei Heng, Jianxiong Gao, Rongxia Xu, et al.
Fatigue & Fracture of Engineering Materials & Structures (2023) Vol. 46, Iss. 5, pp. 1979-1996
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

A novel machine learning method for multiaxial fatigue life prediction: Improved adaptive neuro-fuzzy inference system
Jianxiong Gao, Fei Heng, Yiping Yuan, et al.
International Journal of Fatigue (2023) Vol. 178, pp. 108007-108007
Closed Access | Times Cited: 74
An artificial neural network method for probabilistic life prediction of corroded reinforced concrete
Jianxiong Gao, Haojin Yang
International Journal of Fatigue (2024) Vol. 186, pp. 108418-108418
Closed Access | Times Cited: 14
Machine Learning-Based predictions of crack growth rates in an aeronautical aluminum alloy
Yuval Freed
Theoretical and Applied Fracture Mechanics (2024) Vol. 130, pp. 104278-104278
Closed Access | Times Cited: 13
Uncertainty quantification in multiaxial fatigue life prediction using Bayesian neural networks
GaoYuan He, Yongxiang Zhao, ChuLiang Yan
Engineering Fracture Mechanics (2024) Vol. 298, pp. 109961-109961
Closed Access | Times Cited: 11
Neural network integrated with symbolic regression for multiaxial fatigue life prediction
Peng Zhang, Keke Tang, Anbin Wang, et al.
International Journal of Fatigue (2024) Vol. 188, pp. 108535-108535
Closed Access | Times Cited: 11
Machine learning-based fatigue life prediction of lamellar titanium alloys: A microstructural perspective
Y. Zhao, Yujie Xiang, Keke Tang
Engineering Fracture Mechanics (2024) Vol. 303, pp. 110106-110106
Closed Access | Times Cited: 9
Applications of Long Short-Term Memory (LSTM) Networks in Polymeric Sciences: A Review
Ivan Malashin, В С Тынченко, Andrei Gantimurov, et al.
Polymers (2024) Vol. 16, Iss. 18, pp. 2607-2607
Open Access | Times Cited: 7
A deep learning approach for low-cycle fatigue life prediction under thermal–mechanical loading based on a novel neural network model
Yang Yang, Bo Zhang, Hao Wu, et al.
Engineering Fracture Mechanics (2024) Vol. 306, pp. 110239-110239
Closed Access | Times Cited: 5
Uncertainty analysis of photovoltaic power generation system and intelligent coupling prediction
Guo‐Feng Fan, Yi-Wen Feng, Li‐Ling Peng, et al.
Renewable Energy (2024) Vol. 234, pp. 121174-121174
Closed Access | Times Cited: 5
A frequency domain enhanced multi-view neural network approach to multiaxial fatigue life prediction for various metal materials
Shuonan Chen, Xuhong Zhou, Yongtao Bai
International Journal of Fatigue (2024), pp. 108620-108620
Closed Access | Times Cited: 5
Very high cycle fatigue life prediction of Ti60 alloy based on machine learning with data enhancement
Hongjiang Qian, Zhiyong Huang, Yeting Xu, et al.
Engineering Fracture Mechanics (2023) Vol. 289, pp. 109431-109431
Closed Access | Times Cited: 11
A Novel Physical Neural Network Based on Transformer Framework for Multiaxial Fatigue Life Prediction
Rui Pan, Jianxiong Gao, Yiping Yuan, et al.
Fatigue & Fracture of Engineering Materials & Structures (2025)
Open Access
A fatigue life prediction method based on multi-signal fusion deep attention residual convolutional neural network
Chengying Zhao, Jiajun Wang, Fengxia He, et al.
Applied Acoustics (2025) Vol. 235, pp. 110646-110646
Closed Access
A TCN-based feature fusion framework for multiaxial fatigue life prediction: Bridging loading dynamics and material characteristics
Peng Zhang, Keke Tang
International Journal of Fatigue (2025), pp. 108915-108915
Closed Access
Wind power generation prediction using LSTM model optimized by sparrow search algorithm and firefly algorithm
Wenjing Zhang, Hongjing Yan, Lili Xiang, et al.
Energy Informatics (2025) Vol. 8, Iss. 1
Open Access
Neural network approaches for real-time fatigue life estimation by Surrogating the rainflow counting method
Yu-cheng Guo, Liangxing Li, Jiabin Gui, et al.
International Journal of Fatigue (2025), pp. 108941-108941
Closed Access
Low-Cycle Fatigue Life Prediction of Titanium-Based Intermetallic Alloys Using Machine Learning and Finite Element Analysis
Qiwen Xu, Guoqian Song, Xingwu Li, et al.
Materials (2025) Vol. 18, Iss. 8, pp. 1887-1887
Open Access
A deep learning dataset for metal multiaxial fatigue life prediction
Shuonan Chen, Yongtao Bai, Xuhong Zhou, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 3
Random Forest-Based Fatigue Reliability-Based Design Optimization for Aeroengine Structures
Xueqin Li, Lu-Kai Song
Computer Modeling in Engineering & Sciences (2024) Vol. 140, Iss. 1, pp. 665-684
Open Access | Times Cited: 2
Fatigue life prediction of composite bolted joints based on finite element model and machine learning
Shuai Ma, Kun Tian, Yi Sun, et al.
Fatigue & Fracture of Engineering Materials & Structures (2024) Vol. 47, Iss. 6, pp. 2029-2043
Closed Access | Times Cited: 1
Fusing image and physical data for fatigue life prediction of nickel-based single crystal superalloys
Zhuohan Li, Tianli Zhao, Jing Zhang, et al.
Engineering Failure Analysis (2024) Vol. 162, pp. 108343-108343
Closed Access | Times Cited: 1
Topological optimization and fatigue life prediction of a single pad externally adjustable fluid film bearing
Harishkumar Kamat, Anand Pai, Navaneeth Krishna Vernekar, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Multiaxial fatigue life prediction based on modular neural network pretrained with uniaxial fatigue data
Lei Gan, Anbin Wang, Zheng Zhong, et al.
Engineering Computations (2024)
Closed Access
Physics-Informed Transfer Learning Model for Fatigue Life Prediction of In718 Alloy
Jianfeng Zhang, Baihan Chen, Guangping Zhang, et al.
(2024)
Closed Access
Physics-informed transfer learning model for fatigue life prediction of IN718 alloy
Baihan Chen, J.Q. Zhang, Shangcheng Zhou, et al.
Journal of Materials Research and Technology (2024) Vol. 32, pp. 2767-2779
Open Access
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