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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:

A review on the application of response surface method and artificial neural network in engine performance and exhaust emissions characteristics in alternative fuel
I.M. Yusri, Anwar P. P. Abdul Majeed, Rizalman Mamat, et al.
Renewable and Sustainable Energy Reviews (2018) Vol. 90, pp. 665-686
Closed Access | Times Cited: 183

Showing 1-25 of 183 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
An overview of Higher alcohol and biodiesel as alternative fuels in engines
Erdiwansyah Erdiwansyah, Rizalman Mamat, M. S. M. Sani, et al.
Energy Reports (2019) Vol. 5, pp. 467-479
Open Access | Times Cited: 209
Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions
Masoud Aliramezani, Charles Robert Koch, Mahdi Shahbakhti
Progress in Energy and Combustion Science (2021) Vol. 88, pp. 100967-100967
Closed Access | Times Cited: 190
Optimization of diesel engine operating parameters fueled with palm oil-diesel blend: Comparative evaluation between response surface methodology (RSM) and artificial neural network (ANN)
Samet Uslu
Fuel (2020) Vol. 276, pp. 117990-117990
Closed Access | Times Cited: 155
Machine learning for combustion
Lei Zhou, Yuntong Song, Weiqi Ji, et al.
Energy and AI (2021) Vol. 7, pp. 100128-100128
Open Access | Times Cited: 141
State-of-health estimation of lithium-ion batteries based on electrochemical impedance spectroscopy: a review
Yanshuo Liu, Licheng Wang, Dezhi Li, et al.
Protection and Control of Modern Power Systems (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 137
Applications of artificial intelligence‐based modeling for bioenergy systems: A review
Mochen Liao, Yuan Yao
GCB Bioenergy (2021) Vol. 13, Iss. 5, pp. 774-802
Open Access | Times Cited: 110
A comprehensive review on the effects of diesel/biofuel blends with nanofluid additives on compression ignition engine by response surface methodology
Medhat Elkelawy, E.A. El Shenawy, Hagar Alm‐Eldin Bastawissi, et al.
Energy Conversion and Management X (2022) Vol. 14, pp. 100177-100177
Open Access | Times Cited: 86
Optimized mechanical properties of magnesium matrix composites using RSM and ANN
Bassiouny Saleh, Aibin Ma, Reham Fathi, et al.
Materials Science and Engineering B (2023) Vol. 290, pp. 116303-116303
Closed Access | Times Cited: 45
Machine learning approaches to modeling and optimization of biodiesel production systems: State of art and future outlook
Niyi B. Ishola, Emmanuel I. Epelle, Eriola Betiku
Energy Conversion and Management X (2024) Vol. 23, pp. 100669-100669
Open Access | Times Cited: 17
A review on machine learning forecasting growth trends and their real-time applications in different energy systems
Tanveer Ahmad, Huanxin Chen
Sustainable Cities and Society (2019) Vol. 54, pp. 102010-102010
Closed Access | Times Cited: 143
Performance, combustion, and emission characteristics of a CI engine fueled with emulsified diesel-biodiesel blends at different water contents
W N Maawa, Rizalman Mamat, Gholamhassan Najafi, et al.
Fuel (2020) Vol. 267, pp. 117265-117265
Closed Access | Times Cited: 92
Optimization of diesel engine performance and emission parameters employing cassia tora methyl esters-response surface methodology approach
Yashvir Singh, Abhishek Sharma, Sumit Tiwari, et al.
Energy (2018) Vol. 168, pp. 909-918
Closed Access | Times Cited: 90
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
Optimization of performance and emission parameters of direct injection diesel engine fuelled with pongamia methyl esters-response surface methodology approach
Yashvir Singh, Abhishek Sharma, Gyanendra Kumar Singh, et al.
Industrial Crops and Products (2018) Vol. 126, pp. 218-226
Closed Access | Times Cited: 87
Emerging trends and nanotechnology advances for sustainable biogas production from lignocellulosic waste biomass: A critical review
Muthusamy Govarthanan, S. Manikandan, Ramasamy Subbaiya, et al.
Fuel (2021) Vol. 312, pp. 122928-122928
Closed Access | Times Cited: 81
A comprehensive review of the influence of physicochemical properties of biodiesel on combustion characteristics, engine performance and emissions
Tikendra Nath Verma, Pankaj Shrivastava, Upendra Rajak, et al.
Journal of Traffic and Transportation Engineering (English Edition) (2021) Vol. 8, Iss. 4, pp. 510-533
Open Access | Times Cited: 79
The effect of nano-biochar on the performance and emissions of a diesel engine fueled with fusel oil-diesel fuel
Seyed Mohammad Safieddin Ardebili, Abbas Taghipoor, Hamit Solmaz, et al.
Fuel (2020) Vol. 268, pp. 117356-117356
Closed Access | Times Cited: 71
Critical interpretative review on current outlook and prospects of selective catalytic reduction system for De-NOx strategy in compression ignition engine
R. Vignesh, B. Ashok
Fuel (2020) Vol. 276, pp. 117996-117996
Closed Access | Times Cited: 71
Multi-objective optimization of diesel engine performance, vibration and emission parameters employing blends of biodiesel, hydrogen and cerium oxide nanoparticles with the aid of response surface methodology approach
Osama Khan, Mohd Zaheen Khan, Bhupendra Kumar Bhatt, et al.
International Journal of Hydrogen Energy (2022) Vol. 48, Iss. 56, pp. 21513-21529
Closed Access | Times Cited: 63
Optimization of parameters that affect wear of A356/Al2O3 nanocomposites using RSM, ANN, GA and PSO methods
Blaža Stojаnović, Sandra Gajević, Nenad Kostić, et al.
Industrial Lubrication and Tribology (2022) Vol. 74, Iss. 3, pp. 350-359
Closed Access | Times Cited: 52
Development of artificial neural network and response surface methodology model to optimize the engine parameters of rubber seed oil – Hydrogen on PCCI operation
Edwin Geo Varuvel, Sathyanarayanan Seetharaman, Femilda Josephin Joseph Shobana Bai, et al.
Energy (2023) Vol. 283, pp. 129110-129110
Closed Access | Times Cited: 34
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
Co-gasification of waste triple feed-material blends using downdraft gasifier integrated with dual fuel diesel engine: An RSM-based comparative parametric optimization
Reetu Raj, Jeewan Vachan Tirkey, Deepak Singh, et al.
Journal of the Energy Institute (2023) Vol. 109, pp. 101271-101271
Closed Access | Times Cited: 24
Advanced combustion in heavy fuel aircraft piston engines: A comprehensive review and future directions
Longtao Shao, Yu Zhou, T. Geng, et al.
Fuel (2024) Vol. 370, pp. 131771-131771
Closed Access | Times Cited: 15
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