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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:

Investigation of ANN and SVM based on limited samples for performance and emissions prediction of a CRDI-assisted marine diesel engine
Xiaoxiao Niu, Chuanlei Yang, Hechun Wang, et al.
Applied Thermal Engineering (2016) Vol. 111, pp. 1353-1364
Closed Access | Times Cited: 132

Showing 1-25 of 132 citing articles:

A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
Anh Tuan Hoang, Sandro Nižetić, Hwai Chyuan Ong, et al.
Sustainable Energy Technologies and Assessments (2021) Vol. 47, pp. 101416-101416
Closed Access | Times Cited: 232
Performance and emission prediction of a compression ignition engine fueled with biodiesel-diesel blends: A combined application of ANN and RSM based optimization
Mustafa Aydın, Samet Uslu, Mehmet Çeli̇k
Fuel (2020) Vol. 269, pp. 117472-117472
Closed Access | Times Cited: 197
Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control
Sachin Kumar, T. Gopi, N. Harikeerthana, et al.
Journal of Intelligent Manufacturing (2022) Vol. 34, Iss. 1, pp. 21-55
Open Access | Times Cited: 151
Review of artificial neural networks for gasoline, diesel and homogeneous charge compression ignition engine
Ibham Veza, Asif Afzal, M.A. Mujtaba, et al.
Alexandria Engineering Journal (2022) Vol. 61, Iss. 11, pp. 8363-8391
Open Access | Times Cited: 127
The stability and thermophysical properties of Al2O3-graphene oxide hybrid nanofluids for solar energy applications: Application of robust autoregressive modern machine learning technique
Praveen Kumar Kanti, Prabhakar Sharma, Manoor Prakash Maiya, et al.
Solar Energy Materials and Solar Cells (2023) Vol. 253, pp. 112207-112207
Closed Access | Times Cited: 88
Comparison and evaluation of advanced machine learning methods for performance and emissions prediction of a gasoline Wankel rotary engine
Huaiyu Wang, Changwei Ji, Cheng Shi, et al.
Energy (2022) Vol. 248, pp. 123611-123611
Closed Access | Times Cited: 83
A Review of Modern Machine Learning Techniques in the Prediction of Remaining Useful Life of Lithium-Ion Batteries
Prabhakar Sharma, Bhaskor Jyoti Bora
Batteries (2022) Vol. 9, Iss. 1, pp. 13-13
Open Access | Times Cited: 71
Proportional impact prediction model of animal waste fat-derived biodiesel by ANN and RSM technique for diesel engine
Süleyman Şimşek, Samet Uslu, Hatice Şimsek
Energy (2021) Vol. 239, pp. 122389-122389
Closed Access | Times Cited: 88
A hybrid ANN-Fuzzy approach for optimization of engine operating parameters of a CI engine fueled with diesel-palm biodiesel-ethanol blend
Suman Dey, Narath Moni Reang, Arindam Majumder, et al.
Energy (2020) Vol. 202, pp. 117813-117813
Closed Access | Times Cited: 83
Neural network-based fuel consumption estimation for container ships in Korea
Luan Thanh Le, Gunwoo Lee, Keun-Sik Park, et al.
Maritime Policy & Management (2020) Vol. 47, Iss. 5, pp. 615-632
Closed Access | Times Cited: 75
Artificial neural network approach on forecasting diesel engine characteristics fuelled with waste frying oil biodiesel
D. Babu, Vinoth Thangarasu, Anand Ramanathan
Applied Energy (2020) Vol. 263, pp. 114612-114612
Closed Access | Times Cited: 71
Precise prediction of performance and emission of a waste derived Biogas–Biodiesel powered Dual–Fuel engine using modern ensemble Boosted regression Tree: A critique to Artificial neural network
Prabhakar Sharma, Bibhuti B. Sahoo
Fuel (2022) Vol. 321, pp. 124131-124131
Closed Access | Times Cited: 63
Pre-combustion CO2 capture using amine-based absorption process for blue H2 production from steam methane reformer
Hyun‐Taek Oh, Jaesung Kum, Jun Hyung Park, et al.
Energy Conversion and Management (2022) Vol. 262, pp. 115632-115632
Closed Access | Times Cited: 41
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
A comparative investigation of advanced machine learning methods for predicting transient emission characteristic of diesel engine
Jianxiong Liao, Jie Hu, Fuwu Yan, et al.
Fuel (2023) Vol. 350, pp. 128767-128767
Closed Access | Times Cited: 29
Prediction of the Performance and emission characteristics of diesel engine using diphenylamine Antioxidant and ceria nanoparticle additives with biodiesel based on machine learning
Vijay Kumar, Akhilesh Kumar Choudhary
Energy (2024) Vol. 301, pp. 131746-131746
Closed Access | Times Cited: 13
A general methodology for performance prediction of pumps-as-turbines using Artificial Neural Networks
Mosè Rossi, Massimiliano Renzi
Renewable Energy (2018) Vol. 128, pp. 265-274
Closed Access | Times Cited: 82
Optimization and study of performance parameters in an engine fueled with hydrogen
Javad Zareei, Abbas Rohani
International Journal of Hydrogen Energy (2019) Vol. 45, Iss. 1, pp. 322-336
Closed Access | Times Cited: 63
Application and performance of machine learning techniques in manufacturing sector from the past two decades: A review
Uma Maheshwera Reddy Paturi, Suryapavan Cheruku
Materials Today Proceedings (2020) Vol. 38, pp. 2392-2401
Open Access | Times Cited: 61
Multi-objective optimization of operating parameters for a gasoline Wankel rotary engine by hydrogen enrichment
Changwei Ji, Huaiyu Wang, Cheng Shi, et al.
Energy Conversion and Management (2020) Vol. 229, pp. 113732-113732
Closed Access | Times Cited: 56
ANN modeling for justification of thermodynamic analysis of experimental applications on combustion parameters of a diesel engine using diesel and safflower biodiesel fuels
Bahattin İşcan
Fuel (2020) Vol. 279, pp. 118391-118391
Closed Access | Times Cited: 53
On the use of artificial neural networks to model the performance and emissions of a heavy-duty natural gas spark ignition engine
Qiao Huang, Jinlong Liu, Christopher Ulishney, et al.
International Journal of Engine Research (2021) Vol. 23, Iss. 11, pp. 1879-1898
Closed Access | Times Cited: 49
Comparison and implementation of machine learning models for predicting the combustion phases of hydrogen-enriched Wankel rotary engines
Huaiyu Wang, Changwei Ji, Teng Su, et al.
Fuel (2021) Vol. 310, pp. 122371-122371
Closed Access | Times Cited: 46
Multi-objective optimization of the Atkinson cycle gasoline engine using NSGA Ⅲ coupled with support vector machine and back-propagation algorithm
Yangyang Li, Zhou Shi, Jinping Liu, et al.
Energy (2022) Vol. 262, pp. 125262-125262
Closed Access | Times Cited: 31
The Prediction of Spark-Ignition Engine Performance and Emissions Based on the SVR Algorithm
Yu Zhang, Qifan Wang, Xiaofei Chen, et al.
Processes (2022) Vol. 10, Iss. 2, pp. 312-312
Open Access | Times Cited: 29
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