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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:

Prediction of main particulars of container ships using artificial intelligence algorithms
Darin Majnarić, Sandi Baressi Šegota, Ivan Lorencin, et al.
Ocean Engineering (2022) Vol. 265, pp. 112571-112571
Closed Access | Times Cited: 15

Showing 15 citing articles:

A Novel Short-Term Ship Motion Prediction Algorithm Based on EMD and Adaptive PSO–LSTM with the Sliding Window Approach
Xiaoyu Geng, Yibing Li, Qian Sun
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 3, pp. 466-466
Open Access | Times Cited: 28
Comprehensive evaluation of machine learning models for predicting ship energy consumption based on onboard sensor data
Ailong Fan, Yingqi Wang, Yang Liu, et al.
Ocean & Coastal Management (2023) Vol. 248, pp. 106946-106946
Closed Access | Times Cited: 19
Prediction of Added Resistance of Container Ships in Regular Head Waves Using an Artificial Neural Network
Ivana Martić, Nastia Degiuli, Carlo Giorgio Grlj
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 7, pp. 1293-1293
Open Access | Times Cited: 15
Improvement of Machine Learning-Based Modelling of Container Ship’s Main Particulars with Synthetic Data
Darin Majnarić, Sandi Baressi Šegota, Nikola Anđelić, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 2, pp. 273-273
Open Access | Times Cited: 5
Machine Learning Models for the Prediction of Wind Loads on Containerships
Nastia Degiuli, Carlo Giorgio Grlj, Ivana Martić, et al.
Journal of Marine Science and Engineering (2025) Vol. 13, Iss. 3, pp. 417-417
Open Access
The use of a set of artificial neural networks to predict added resistance in head waves at the parametric ship design stage
Tomasz Cepowski
Ocean Engineering (2023) Vol. 281, pp. 114744-114744
Open Access | Times Cited: 7
Regression analysis for container ships in the early design stage
Barbara Rinauro, Ermina Begović, Francesco Mauro, et al.
Ocean Engineering (2023) Vol. 292, pp. 116499-116499
Open Access | Times Cited: 6
Use of Synthetic Data in Maritime Applications for the Problem of Steam Turbine Exergy Analysis
Sandi Baressi Šegota, Vedran Mrzljak, Nikola Anđelić, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 8, pp. 1595-1595
Open Access | Times Cited: 5
Artificial Neural Network-Based Prediction of the Extreme Response of Floating Offshore Wind Turbines under Operating Conditions
Wang Ke-lin, Oleg Gaidai, Fang Wang, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 9, pp. 1807-1807
Open Access | Times Cited: 5
Comparison of model selection and data bias on the prediction performance of purpleback flying squid (Sthenoteuthis oualaniensis) fishing ground in the Northwest Indian Ocean
Haibin Han, Bohui Jiang, Delong Xiang, et al.
Ecological Indicators (2024) Vol. 158, pp. 111526-111526
Open Access | Times Cited: 1
Navigation risk assessment of intelligent ships based on DS-Fuzzy weighted distance Bayesian network
Wenjun Zhang, Yingjun Zhang, Chuang Zhang
Ocean Engineering (2024) Vol. 313, pp. 119452-119452
Closed Access | Times Cited: 1
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
Artificial Neural Network Approach for Main Engine Power Prediction of General Cargo Vessels
Emrullah Çirçir, Samet Gürgen
Mersin Üniversitesi Denizcilik ve Lojistik Araştırmaları Dergisi (2024)
Closed Access
Prediction of main engine power of oil tankers using artificial intelligence algorithms
Darin Majnarić, Nikola Anđelić, Sandi Baressi Šegota, et al.
IMDC. (2024)
Open Access
SURROGATE MODEL BASED ON ARTIFICIAL NEURAL NETWORK FOR THE FAST PREDICTION OF HYDRODYNAMIC RESISTANCE FOR BULBOUS BOW VESSELS
Samuel Ruiz-Capel, Aase Reyes, Dimitris Kraniotis
(2023), pp. 1-9
Open Access
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