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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 IC engine performance and emission parameters using machine learning: A review
K. Karunamurthy, Ayub Ahmed Janvekar, P. L. Palaniappan, et al.
Journal of Thermal Analysis and Calorimetry (2023) Vol. 148, Iss. 9, pp. 3155-3177
Closed Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
Van Nhanh Nguyen, W. Tarełko, Prabhakar Sharma, et al.
Energy & Fuels (2024) Vol. 38, Iss. 3, pp. 1692-1712
Closed Access | Times Cited: 49
Data-driven optimization of turbulent kinetic energy and tumble-y in combustion engines: A comparative study of machine learning models
Amirali Shateri, Zhiyin Yang, Yun Liu, et al.
Fuel (2025) Vol. 389, pp. 134590-134590
Open Access | Times Cited: 2
A Novel Forecasting Framework Leveraging Large Language Model and Machine Learning for Methanol Price
Wenyang Wang, Yuping Luo, Mingrui Ma, et al.
Energy (2025), pp. 135123-135123
Closed Access | Times Cited: 2
Prediction of combustion, performance, and emission parameters of ethanol powered spark ignition engine using ensemble Least Squares boosting machine learning algorithms
D. Jesu Godwin, Edwin Geo Varuvel, Leenus Jesu Martin
Journal of Cleaner Production (2023) Vol. 421, pp. 138401-138401
Closed Access | Times Cited: 32
Using Artificial Neural Networks for Predicting Ship Fuel Consumption
Van Giao Nguyen, R. Sakthivel, Krzysztof Rudzki, et al.
Polish Maritime Research (2023) Vol. 30, Iss. 2, pp. 39-60
Open Access | Times Cited: 28
Improving Diesel Engine Reliability Using an Optimal Prognostic Model to Predict Diesel Engine Emissions and Performance Using Pure Diesel and Hydrogenated Vegetable Oil
Tadas Žvirblis, Jacek Hunicz, Jonas Matijošius, et al.
Eksploatacja i Niezawodnosc - Maintenance and Reliability (2023) Vol. 25, Iss. 4
Open Access | Times Cited: 15
Optimization of performance and emission of a diesel engine fueled with isopropyl alcohol Blends: A comparative ANN-GA and RSM-HCO application
Mehmet Şen
Engineering Science and Technology an International Journal (2024) Vol. 55, pp. 101733-101733
Open Access | Times Cited: 5
Experimental investigation and optimization of performance, emission, and vibro-acoustic parameters of SI engine fueled with n-propanol and gasoline blends using ANN-GA coupled with NSGA3-modified TOPSIS hybrid approach
K. R. Kirankumar, Gunasekaran Kumar, Nagaraja Kamath, et al.
Energy (2024) Vol. 306, pp. 132521-132521
Closed Access | Times Cited: 5
Data-driven enabling technologies in soft sensors of modern internal combustion engines: Perspectives
Ji Li, Quan Zhou, Xu He, et al.
Energy (2023) Vol. 272, pp. 127067-127067
Open Access | Times Cited: 13
Prediction of transient emission characteristic from diesel engines based on CNN-GRU model optimized by PSO algorithm
Jianxiong Liao, Jie Hu, Peng Chen, et al.
Energy Sources Part A Recovery Utilization and Environmental Effects (2024) Vol. 46, Iss. 1, pp. 1800-1818
Closed Access | Times Cited: 4
Prediction of toxic compounds emissions in exhaust gases based on engine vibration and Bayesian optimized decision trees
Piotr Bortnowski, Jędrzej Matla, Gustaw Sierzputowski, et al.
Measurement (2024) Vol. 235, pp. 115018-115018
Closed Access | Times Cited: 4
Development of comprehensive models for precise prognostics of ship fuel consumption
Thanh Tuan Le, Prabhakar Sharma, Nguyen Dang Khoa Pham, et al.
Journal of Marine Engineering & Technology (2024) Vol. 23, Iss. 6, pp. 451-465
Closed Access | Times Cited: 4
Study on Carbon Emission Influencing Factors and Carbon Emission Reduction Potential in China's Food Production Industry
Yuanping Wang, Lang Hu, Lingchun Hou, et al.
Environmental Research (2024) Vol. 261, pp. 119702-119702
Closed Access | Times Cited: 4
Role of hydrogen-enrichment on performance and emission characteristics of a diesel engine fuelled with metal oxide nanoparticles added biodiesel/diesel blends:A combined neuro Fuzzy-Gaussian Mixture Model analysis
Osama Khan, Ibrahim Alsaduni, Mohd Parvez, et al.
International Journal of Hydrogen Energy (2024) Vol. 93, pp. 1113-1126
Closed Access | Times Cited: 4
Data-driven modeling for predicting the steady-state and transient performance of a dual-fuel medium-duty engine employing artificial neural networks
Antonio G. Garcı́a, Javier Monsalve‐Serrano, Javier Marco-Gimeno, et al.
Fuel (2025) Vol. 394, pp. 135150-135150
Closed Access
Machine learning-driven prediction and optimization of selective glycerol electrocatalytic reduction into propanediols
M.M. Harussani, Cries Avian, Shuo Cheng, et al.
Journal of Electroanalytical Chemistry (2025) Vol. 988, pp. 119150-119150
Closed Access
Identifying key soil and landscape factors influencing yield spatial patterns for management zone delineation using ensemble machine learning
Yue Li, Yuxin Miao, Ankit Singh Rawat, et al.
Computers and Electronics in Agriculture (2025) Vol. 237, pp. 110487-110487
Closed Access
Experimental investigation of features of CI engine fueled with blends of camphor oil with biomass waste simarouba glauca oil
Manikandaraja Gurusamy, Mathanraj Vijayaragavan, Edwin Geo Varuvel
Energy Sources Part A Recovery Utilization and Environmental Effects (2024) Vol. 46, Iss. 1, pp. 3884-3901
Closed Access | Times Cited: 3
Integrating Machine Learning for Predicting Internal Combustion Engine Performance and Segment-Based CO2 Emissions Across Urban and Rural Settings
Naghmeh Niroomand, Christian Bach
IEEE Access (2024) Vol. 12, pp. 66223-66236
Open Access | Times Cited: 3
An advanced high dimensional model representation approach for internal combustion engine modeling and optimization
Jianhong Lei, Jing Li, Shaohua Wu, et al.
Energy (2024) Vol. 311, pp. 133409-133409
Closed Access | Times Cited: 3
Evaluation of engine performance and emissions using blends of gasoline, ethanol, and fusel oil
S.M. Rosdi, Erdiwansyah Erdiwansyah, Mohd Fairusham Ghazali, et al.
Case Studies in Chemical and Environmental Engineering (2024), pp. 101065-101065
Open Access | Times Cited: 3
Application of an explainable glass-box machine learning approach for prognostic analysis of a biogas-powered small agriculture engine
Mehdi Jamei, Prabhakar Sharma, Mumtaz Ali, et al.
Energy (2023) Vol. 288, pp. 129862-129862
Closed Access | Times Cited: 7
Prediction of combustion pressure with deep learning using flame images
Ahmed Maged, Mohamed Nour
Fuel (2024) Vol. 380, pp. 133203-133203
Closed Access | Times Cited: 2
Prognostic Metamodel Development for Waste-Derived Biogas-Powered Dual-Fuel Engines Using Modern Machine Learning with K-Cross Fold Validation
Mansoor Alruqi, H. A. Hanafi, Prabhakar Sharma
Fermentation (2023) Vol. 9, Iss. 7, pp. 598-598
Open Access | Times Cited: 4
An ensemble learning algorithm for optimization of spark ignition engine performance fuelled with methane/hydrogen blends
Mohammad-Hassan Tayarani-Najaran, Amin Paykani
Applied Soft Computing (2024), pp. 112468-112468
Open Access | Times Cited: 1
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