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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:

Fuel Consumption Prediction Models Based on Machine Learning and Mathematical Methods
Xianwei Xie, Baozhi Sun, Xiaohe Li, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 4, pp. 738-738
Open Access | Times Cited: 16

Showing 16 citing articles:

Application, opportunities, and challenges of digital technologies in the decarbonizing shipping industry: a bibliometric analysis
Guangnian Xiao, Lei Pan, Fengbo Lai
Frontiers in Marine Science (2025) Vol. 12
Open Access | Times Cited: 9
Short-term forecasting for ship fuel consumption based on deep learning
Yumei Chen, Baozhi Sun, Xianwei Xie, et al.
Ocean Engineering (2024) Vol. 301, pp. 117398-117398
Closed Access | Times Cited: 10
DenseNet-Enabled Intelligent Ship Energy Consumption Prediction Method with Navigation Information and Environmental Factors
Ganqi Tang, Rui Luo, Bin Huang, et al.
Machines (2025) Vol. 13, Iss. 2, pp. 76-76
Open Access
An Adaptive Prediction Framework of Ship Fuel Consumption for Dynamic Maritime Energy Management
Gao Ya, Yanghui Tan, Dingyu Jiang, et al.
Journal of Marine Science and Engineering (2025) Vol. 13, Iss. 3, pp. 409-409
Open Access
Research on speed optimization of fixed route ship with low data dependence
Chaodong Hu, Yu Wang, Xu Han, et al.
Ocean Engineering (2025) Vol. 328, pp. 121065-121065
Closed Access
Joint optimization of ship speed and trim based on machine learning method under consideration of load
Xianwei Xie, Baozhi Sun, Xiaohe Li, et al.
Ocean Engineering (2023) Vol. 287, pp. 115917-115917
Closed Access | Times Cited: 9
Improving Ship Fuel Consumption and Carbon Intensity Prediction Accuracy Based on a Long Short-Term Memory Model with Self-Attention Mechanism
Zhihuan Wang, Tianye Lu, Yi Han, et al.
Applied Sciences (2024) Vol. 14, Iss. 18, pp. 8526-8526
Open Access | Times Cited: 2
Research on Carbon Intensity Prediction Method for Ships Based on Sensors and Meteorological Data
Chunchang Zhang, Tianye Lu, Zhihuan Wang, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 12, pp. 2249-2249
Open Access | Times Cited: 5
Unraveling Energy Consumption patterns: Insights through Data Analysis and Predictive Modeling
Neda Maleki, Xianwei Xie, Arslan Musaddiq, et al.
(2024)
Open Access | Times Cited: 1
Utilizing Machine Learning Approach to Forecast Fuel Consumption of Backhoe Loader Equipment
Poonam Katyare, Shubhalaxmi Joshi, Mrudula Kulkarni
International Journal of Advanced Computer Science and Applications (2024) Vol. 15, Iss. 5
Open Access | Times Cited: 1
Analysis of the Use and Application of Mathematics in Economics: Demand and Supply Functions
Andrew Satria Lubis, Zulfan Zulfan, Mutia Fitri Chania, et al.
Journal of Research in Mathematics Trends and Technology (2024) Vol. 6, Iss. 1, pp. 16-23
Open Access
Interpretable Machine Learning: A Case Study on Predicting Fuel Consumption in VLGC Ship Propulsion
Aleksandar Vorkapić, Sanda Martinčić-Ipšić, Rok Piltaver
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 10, pp. 1849-1849
Open Access
Prediction of Ship Main Particulars for Harbor Tugboats Using a Bayesian Network Model and Non-Linear Regression
Ömer Emre Karaçay, Çağlar Karatuğ, Tayfun Uyanık, et al.
Applied Sciences (2024) Vol. 14, Iss. 7, pp. 2891-2891
Open Access
An Innovative Deep-Learning Technique for Fuel Demand Estimation in Maritime Transportation: A Step Toward Sustainable Development and Environmental Impact Mitigation
Ayman F. Alghanmi, Bassam M. Aljahdali, Hussain T. Sulaimani, et al.
Water (2024) Vol. 16, Iss. 22, pp. 3325-3325
Open Access
Short-Term Forcasting for Ship Fuel Consumption Based on Deep Learning
Yumei Chen, Baozhi Sun, Xianwei Xie, et al.
(2023)
Closed Access
Data-driven Fuel Flow Prediction Model for Aircraft Engines
Ahmed Salem Ahmed Al-Khanbashi, Jing Cai
(2023), pp. 279-283
Closed Access
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