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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 deep learning method for the prediction of 6-DoF ship motions in real conditions
Mingyang Zhang, Ghalib Taimuri, Jinfen Zhang, et al.
Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment (2023) Vol. 237, Iss. 4, pp. 887-905
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Research in marine accidents: A bibliometric analysis, systematic review and future directions
Yuhao Cao, Xinjian Wang, Zaili Yang, et al.
Ocean Engineering (2023) Vol. 284, pp. 115048-115048
Open Access | Times Cited: 85
A machine learning method for the prediction of ship motion trajectories in real operational conditions
Mingyang Zhang, Pentti Kujala, Mashrura Musharraf, et al.
Ocean Engineering (2023) Vol. 283, pp. 114905-114905
Open Access | Times Cited: 65
Ship trajectory prediction based on machine learning and deep learning: A systematic review and methods analysis
Huanhuan Li, Hang Jiao, Zaili Yang
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107062-107062
Open Access | Times Cited: 60
A deep learning method for the prediction of ship fuel consumption in real operational conditions
Mingyang Zhang, Nikolaos Tsoulakos, Pentti Kujala, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 130, pp. 107425-107425
Open Access | Times Cited: 57
Maritime traffic partitioning: An adaptive semi-supervised spectral regularization approach for leveraging multi-graph evolutionary traffic interactions
Xuri Xin, Kezhong Liu, Huanhuan Li, et al.
Transportation Research Part C Emerging Technologies (2024) Vol. 164, pp. 104670-104670
Open Access | Times Cited: 25
Analysis of human errors in human-autonomy collaboration in autonomous ships operations through shore control experimental data
Tingting Cheng, E. Veitch, Ingrid Bouwer Utne, et al.
Reliability Engineering & System Safety (2024) Vol. 246, pp. 110080-110080
Open Access | Times Cited: 21
Multi-scale collision risk estimation for maritime traffic in complex port waters
Xuri Xin, Kezhong Liu, Sean Loughney, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109554-109554
Open Access | Times Cited: 35
Deep learning-based object detection in maritime unmanned aerial vehicle imagery: Review and experimental comparisons
Chenjie Zhao, Ryan Wen Liu, Jingxiang Qu, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 128, pp. 107513-107513
Open Access | Times Cited: 35
Graph-based ship traffic partitioning for intelligent maritime surveillance in complex port waters
Xuri Xin, Kezhong Liu, Sean Loughney, et al.
Expert Systems with Applications (2023) Vol. 231, pp. 120825-120825
Open Access | Times Cited: 25
A Review on Motion Prediction for Intelligent Ship Navigation
Daiyong Zhang, Xiumin Chu, Chenguang Liu, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 1, pp. 107-107
Open Access | Times Cited: 11
A hybrid deep learning method for the prediction of ship time headway using automatic identification system data
Quandang Ma, Xu Du, Cong Liu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108172-108172
Open Access | Times Cited: 9
A review on the hydrodynamics of planing hulls
Sasan Tavakoli, Mingyang Zhang, Aleksander A. Kondratenko, et al.
Ocean Engineering (2024) Vol. 303, pp. 117046-117046
Open Access | Times Cited: 9
Spatio-temporal multi-graph transformer network for joint prediction of multiple vessel trajectories
Ryan Wen Liu, Weixin Zheng, Maohan Liang
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107625-107625
Closed Access | Times Cited: 17
PSO-Based Predictive PID-Backstepping Controller Design for the Course-Keeping of Ships
Bowen Lin, Mao Zheng, Bing Han, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 2, pp. 202-202
Open Access | Times Cited: 6
SFT-Net: A Network for Detecting Fatigue From EEG Signals by Combining 4D Feature Flow and Attention Mechanism
Dongrui Gao, Kejie Wang, Manqing Wang, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 28, Iss. 8, pp. 4444-4455
Closed Access | Times Cited: 15
A hybrid prediction model of vessel trajectory based on attention mechanism and CNN-GRU
Jian Cen, JiaXi Li, Xi Liu, et al.
Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment (2024) Vol. 238, Iss. 4, pp. 809-823
Closed Access | Times Cited: 5
Online ship motion identification modeling and its application to course-keeping control
Yao Meng, Xianku Zhang, Xiufeng Zhang, et al.
Ocean Engineering (2024) Vol. 294, pp. 116853-116853
Closed Access | Times Cited: 4
COLREGs-Adaptive trajectory planning and decision-making in maritime autonomous surface ships
Zhepeng Han, Da Wu, Jinfen Zhang, et al.
Ocean Engineering (2024) Vol. 312, pp. 119308-119308
Closed Access | Times Cited: 4
Part B: Innovative Data Augmentation Approach to Boost Machine Learning for Hydrodynamic Purposes— Computational Efficiency
Hamed Majidian, Hossein Enshaei, Damon Howe, et al.
Applied Sciences (2025) Vol. 15, Iss. 1, pp. 346-346
Open Access
A hybrid deep learning method for the real-time prediction of collision damage consequences in operational conditions
Mingyang Zhang, Hongdong Wang, Fabien Conti, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 145, pp. 110158-110158
Open Access
Incorporating prior knowledge of collision risk into deep learning networks for ship trajectory prediction in the maritime Internet of Things industry
Yu Zhang, Ping Tu, Zhiyuan Zhao, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 146, pp. 110311-110311
Closed Access
Parameter Prediction of the Non-Linear Nomoto Model for Different Ship Loading Conditions Using Support Vector Regression
Jiafen Lan, Mao Zheng, Xiumin Chu, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 5, pp. 903-903
Open Access | Times Cited: 9
Cognitive knowledge graph generation for grid fault handling based on attention mechanism combined with multi-modal factor fusion
Zhenbin Li, Zhigang Huang, Lingxu Guo, et al.
Computers & Electrical Engineering (2023) Vol. 111, pp. 108855-108855
Open Access | Times Cited: 8
A novel method for the evaluation of ship berthing risk using AIS data
Bowen Lin, Mao Zheng, Xiumin Chu, et al.
Ocean Engineering (2023) Vol. 293, pp. 116595-116595
Closed Access | Times Cited: 8
Prediction of Ship Traffic Flow and Congestion Based on Extreme Learning Machine with Whale Optimization Algorithm and Fuzzy c-Means Clustering
Yongjun Chen, Ming Huang, Kaixuan Song, et al.
Journal of Advanced Transportation (2023) Vol. 2023, pp. 1-12
Open Access | Times Cited: 7
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