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 Model for the Viscosity of Heavy Oil Diluted with Light Oil Using Machine Learning Techniques
Xiaodong Gao, Pingchuan Dong, Jiawei Cui, et al.
Energies (2022) Vol. 15, Iss. 6, pp. 2297-2297
Open Access | Times Cited: 14

Showing 14 citing articles:

Catalytic production of light Olefins: Perspective and prospective
Naif Almuqati, Afrah M. Aldawsari, Khalid N. Alharbi, et al.
Fuel (2024) Vol. 366, pp. 131270-131270
Open Access | Times Cited: 23

An assessment of ensemble learning approaches and single-based machine learning algorithms for the characterization of undersaturated oil viscosity
Theddeus T. Akano, Chinemerem C. James
Beni-Suef University Journal of Basic and Applied Sciences (2022) Vol. 11, Iss. 1
Open Access | Times Cited: 17

Optimisation Methodology for Skimmer Device Selection for Removal of the Marine Oil Pollution
Marko Đorđević, Đani Šabalja, Đani Mohović, et al.
Journal of Marine Science and Engineering (2022) Vol. 10, Iss. 7, pp. 925-925
Open Access | Times Cited: 14

Prediction of Viscosity of Blends of Heavy Oils with Diluents by Empirical Correlations and Artificial Neural Network
Dicho Stratiev, Svetoslav Nenov, Ivelina Shishkova, et al.
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 49, pp. 21449-21463
Closed Access | Times Cited: 7

Study of the precipitation trend of asphaltenes and waxes in crude oil using computational chemistry and statistical thermodynamics methods
Edgardo Jonathan Suárez-Domínguez, Josúe Francisco Pérez-Sánchez, Hugo Herrera-Pilotzi, et al.
Results in Engineering (2023) Vol. 21, pp. 101672-101672
Open Access | Times Cited: 6

Prediction of significant oil properties using image processing based on RGB pixel intensity
Aditya Kolakoti, Ruthvik Chandramouli
Fuel (2023) Vol. 349, pp. 128618-128618
Closed Access | Times Cited: 5

Determination of Wax Deposition Rate Model of Blended Oils with Different Blending Ratios
Zhuo Han, Lihui Ma, Xiaowei Li, et al.
Processes (2024) Vol. 12, Iss. 4, pp. 772-772
Open Access | Times Cited: 1

Foam Systems for Enhancing Heavy Oil Recovery by Double Improving Mobility Ratio
Chao Chen, Hao Xu, Lidong Zhang, et al.
Processes (2023) Vol. 11, Iss. 10, pp. 2961-2961
Open Access | Times Cited: 4

Comparative Analysis of Soft Computing Models for Predicting Viscosity in Diesel Engine Lubricants: An Alternative Approach to Condition Monitoring
Mohammad-Reza Pourramezan, Abbas Rohani, Mohammad Hossein Abbaspour‐Fard
ACS Omega (2023)
Open Access | Times Cited: 3

Fluid viscosity prediction leveraging computer vision and robot interaction
J. Park, Gauri Pramod Dalwankar, Alison Bartsch, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108603-108603
Open Access

Virtualized Viscosity Sensor for Onboard Energy Management
Nicolas Gascoin, Pascal Valade
Energies (2024) Vol. 17, Iss. 15, pp. 3635-3635
Open Access

Application of artificial intelligence technology in unconventional natural gas production forecasting
Qichao Gao, Lulu Liao, Shunhui Yang
Third International Conference on Computer Science and Communication Technology (ICCSCT 2022) (2022)
Open Access | Times Cited: 2

Hierarchical Optimization of Oil Spill Response Vessels in Cases of Accidental Pollution of Bays and Coves
Marko Đorđević, Đani Mohović, Antoni Krišković, et al.
Journal of Marine Science and Engineering (2022) Vol. 10, Iss. 6, pp. 772-772
Open Access | Times Cited: 1

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