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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:

Deep learning-powered vessel traffic flow prediction with spatial-temporal attributes and similarity grouping
Yan Li, Maohan Liang, Huanhuan Li, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107012-107012
Open Access | Times Cited: 19

Showing 19 citing articles:

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: 55
Deep bi-directional information-empowered ship trajectory prediction for maritime autonomous surface ships
Huanhuan Li, Wenbin Xing, Hang Jiao, et al.
Transportation Research Part E Logistics and Transportation Review (2023) Vol. 181, pp. 103367-103367
Open Access | Times Cited: 28
MFOA-Bi-LSTM: An optimized bidirectional long short-term memory model for short-term traffic flow prediction
Bharti Naheliya, Poonam Redhu, Kranti Kumar
Physica A Statistical Mechanics and its Applications (2023) Vol. 634, pp. 129448-129448
Closed Access | Times Cited: 28
AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods
Muhammad Usman Tariq, Shuhaida Ismail
Osong Public Health and Research Perspectives (2024) Vol. 15, Iss. 2, pp. 115-136
Open Access | Times Cited: 12
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: 8
Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories
Yan Li, Huanhuan Li, Chao Zhang, et al.
Transportation Research Part C Emerging Technologies (2024) Vol. 163, pp. 104648-104648
Open Access | Times Cited: 8
Residual attention enhanced Time-varying Multi-Factor Graph Convolutional Network for traffic flow prediction
Yinxin Bao, Qin-Qin Shen, Yang Cao, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108135-108135
Closed Access | Times Cited: 7
Deep multi-view information-powered vessel traffic flow prediction for intelligent transportation management
Huanhuan Li, Yu Zhang, Yan Li, et al.
Transportation Research Part E Logistics and Transportation Review (2025) Vol. 197, pp. 104072-104072
Open Access
A spatial-temporal attention method for the prediction of multi ship time headways using AIS data
Quandang Ma, Xu Du, Mingyang Zhang, et al.
Ocean Engineering (2024) Vol. 311, pp. 118927-118927
Open Access | Times Cited: 3
A hierarchical methodology for vessel traffic flow prediction using Bayesian tensor decomposition and similarity grouping
Wenbin Xing, Jingbo Wang, Kaiwen Zhou, et al.
Ocean Engineering (2023) Vol. 286, pp. 115687-115687
Open Access | Times Cited: 8
A Short-Term Vessel Traffic Flow Prediction Based on a DBO-LSTM Model
Ze Dong, Yipeng Zhou, Xiongguan Bao
Sustainability (2024) Vol. 16, Iss. 13, pp. 5499-5499
Open Access | Times Cited: 2
Geohash coding-powered deep learning network for vessel trajectory prediction using clustered AIS data in maritime Internet of Things industries
Yan Li, Bi Yu Chen, Qi Liu, et al.
Computers & Electrical Engineering (2024) Vol. 120, pp. 109611-109611
Closed Access | Times Cited: 2
An expert system for privacy-driven vessel detection harnessing YOLOv8 and strengthened by SHA-256
Naga Venkata Rishika Guggilam, Ch. Rupa, Akhil Babu Nambur, et al.
Computers & Security (2024) Vol. 143, pp. 103902-103902
Closed Access | Times Cited: 2
TG-PGAT: An AIS Data-Driven Dynamic Spatiotemporal Prediction Model for Ship Traffic Flow in the Port
Jianwen Ma, Yue Zhou, Yuhsuan Chang, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 10, pp. 1875-1875
Open Access | Times Cited: 2
EF-former for Short-Term Passenger Flow Prediction During Large-Scale Events in Urban Rail Transit Systems
Jinlei Zhang, Shuai Mao, Shuxin Zhang, et al.
Information Fusion (2024), pp. 102916-102916
Closed Access | Times Cited: 2
Deep learning innovations in South Korean maritime navigation: Enhancing vessel trajectories prediction with AIS data
Umar Zaman, Junaid Khan, Eunkyu Lee, et al.
PLoS ONE (2024) Vol. 19, Iss. 10, pp. e0310385-e0310385
Open Access | Times Cited: 1
End-to-end model-based trajectory prediction for ro-ro ship route using dual-attention mechanism
Licheng Zhao, Yi Zuo, Wenjun Zhang, et al.
Frontiers in Computational Neuroscience (2024) Vol. 18
Open Access | Times Cited: 1
Adaptive genetic algorithm-optimized temporal convolutional networks for high-precision ship traffic flow prediction
Yunfan Li, Haijun Wang
Evolving Systems (2024) Vol. 16, Iss. 1
Closed Access | Times Cited: 1
Using LSTM with Trajectory Point Correlation and Temporal Pattern Attention for Ship Trajectory Prediction
Yi Zhou, Haitao Guo, Jun Lu, et al.
Electronics (2024) Vol. 13, Iss. 23, pp. 4705-4705
Open Access
Analysis of vessel traffic flow characteristics in inland restricted waterways using multi-source data
Wenzhang Yang, Peng Liao, Shangkun Jiang, et al.
Ocean Engineering (2024) Vol. 317, pp. 120065-120065
Closed Access
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