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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:

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

Showing 1-25 of 71 citing articles:

Machine learning technology in biodiesel research: A review
Mortaza Aghbashlo, Wanxi Peng, Meisam Tabatabaei, et al.
Progress in Energy and Combustion Science (2021) Vol. 85, pp. 100904-100904
Closed Access | Times Cited: 348
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
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
Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms
Ehsan Elahi, Zhixin Zhang, Zainab Khalid, et al.
Energy (2022) Vol. 244, pp. 123169-123169
Closed Access | Times Cited: 118
Comparison of neural network and response surface methodology techniques on optimization of biodiesel production from mixed waste cooking oil using heterogeneous biocatalyst
Babu Dharmalingam, S. Balamurugan, Unalome Wetwatana, et al.
Fuel (2023) Vol. 340, pp. 127503-127503
Closed Access | Times Cited: 53
Application of Artificial Neural Network for Internal Combustion Engines: A State of the Art Review
Aditya Narayan Bhatt, Nitin Shrivastava
Archives of Computational Methods in Engineering (2021) Vol. 29, Iss. 2, pp. 897-919
Open Access | Times Cited: 73
Comparative study using RSM and ANN modelling for performance-emission prediction of CI engine fuelled with bio-diesohol blends: A fuzzy optimization approach
Suman Dey, Narath Moni Reang, Pankaj Kumar Das, et al.
Fuel (2021) Vol. 292, pp. 120356-120356
Closed Access | Times Cited: 71
A critical review of recent advancements in continuous flow reactors and prominent integrated microreactors for biodiesel production
R. Gopi, Vinoth Thangarasu, Angkayarkan Vinayakaselvi M, et al.
Renewable and Sustainable Energy Reviews (2021) Vol. 154, pp. 111869-111869
Closed Access | Times Cited: 62
Dual fuel combustion of 1-hexanol with diesel and biodiesel fuels in a diesel engine: An experimental investigation and multi criteria optimization using artificial neural network and TOPSIS algorithm
T. Anandavelu, Sundararajan Rajkumar, Vinoth Thangarasu
Fuel (2023) Vol. 338, pp. 127318-127318
Closed Access | Times Cited: 25
Use of Artificial Neural Networks to Predict Fuel Consumption on the Basis of Technical Parameters of Vehicles
Jarosław Ziółkowski, Mateusz Oszczypała, Jerzy Małąchowski, et al.
Energies (2021) Vol. 14, Iss. 9, pp. 2639-2639
Open Access | Times Cited: 56
Robust and general predictive models for condensation heat transfer inside conventional and mini/micro channel heat exchangers
M.A. Moradkhani, Seyyed Hossein Hosseini, Mengjie Song
Applied Thermal Engineering (2021) Vol. 201, pp. 117737-117737
Closed Access | Times Cited: 49
Support vector regression approach to optimize the biodiesel composition for improved engine performance and lower exhaust emissions
Kiran Raj Bukkarapu, Anand Krishnasamy
Fuel (2023) Vol. 348, pp. 128604-128604
Closed Access | Times Cited: 21
Artificial neural network models for forecasting the combustion and emission characteristics of ethanol/gasoline DFSI engines with combined injection strategy
Ping Sun, Xiqing Cheng, Yang Song, et al.
Case Studies in Thermal Engineering (2024) Vol. 54, pp. 104007-104007
Open Access | Times Cited: 7
Performance improvement of compression ignition engine fueled by second generation biodiesel fuel blends enriched with ZnO nanoparticles: Experimental study and Gaussian process regression AI modeling
Mohammed El-Adawy, Mohamed E. Zayed, Bashar Shboul, et al.
Process Safety and Environmental Protection (2024) Vol. 190, pp. 1372-1385
Closed Access | Times Cited: 7
Prediction of emission characteristics of a diesel engine using experimental and artificial neural networks
Tran Van Hung, Hussein H. Alkhamis, Abdulwahed Fahad Alrefaei, et al.
Applied Nanoscience (2021) Vol. 13, Iss. 1, pp. 433-442
Closed Access | Times Cited: 40
Application of Elman and Cascade neural network (ENN and CNN) in comparison with adaptive neuro fuzzy inference system (ANFIS) to predict key fuel properties of ABE-diesel blends
Ibham Veza, Mohd Farid Muhamad Said, Zulkarnain Abdul Latiff, et al.
International Journal of Green Energy (2021) Vol. 18, Iss. 14, pp. 1510-1522
Closed Access | Times Cited: 34
Combustion, performance, and emission behavior of a CI engine fueled with different biodiesels: A modelling, forecasting and experimental study
Vivek Kumar Nema, Alok Singh, Prem Kumar Chaurasiya, et al.
Fuel (2022) Vol. 339, pp. 126976-126976
Closed Access | Times Cited: 26
Neuro-Particle Swarm Optimization Based In-Situ Prediction Model for Heavy Metals Concentration in Groundwater and Surface Water
Kevin Lawrence M. de Jesus, Delia B. Senoro, Jennifer C. Dela Cruz, et al.
Toxics (2022) Vol. 10, Iss. 2, pp. 95-95
Open Access | Times Cited: 24
Experimental and empirical analysis of a diesel engine fuelled with ternary blends of diesel, waste cooking sunflower oil biodiesel and diethyl ether
B. Devaraj Naik, Udayakumar Meivelu, Vinoth Thangarasu, et al.
Fuel (2022) Vol. 320, pp. 123961-123961
Closed Access | Times Cited: 23
The current state applications of ethyl carbonate with ionic liquid in sustainable biodiesel production: A review
Balaji Panchal, Zheng Zhu, Shenjun Qin, et al.
Renewable Energy (2021) Vol. 181, pp. 341-354
Closed Access | Times Cited: 30
Experimental Investigation and Neural network based parametric prediction in a multistage reciprocating humidifier
Sampath Suranjan Salins, S.V. Kota Reddy, Shiva Kumar
Applied Energy (2021) Vol. 293, pp. 116958-116958
Closed Access | Times Cited: 28
A Hybrid Neural Network–Particle Swarm Optimization Informed Spatial Interpolation Technique for Groundwater Quality Mapping in a Small Island Province of the Philippines
Kevin Lawrence M. de Jesus, Delia B. Senoro, Jennifer C. Dela Cruz, et al.
Toxics (2021) Vol. 9, Iss. 11, pp. 273-273
Open Access | Times Cited: 28
An improved A-ECMS energy management for plug-in hybrid electric vehicles considering transient characteristics of engine
Hongwen He, Yiwen Shou, Jian Song
Energy Reports (2023) Vol. 10, pp. 2006-2016
Open Access | Times Cited: 12
A neural network approach on forecasting spark duration effect on in-cylinder performance of a large bore compression ignition engine fueled with propane direct injection
Cahyani Windarto, Ocktaeck Lim
Fuel Processing Technology (2024) Vol. 257, pp. 108088-108088
Open Access | Times Cited: 4
An investigation of hybrid models FEA coupled with AHP-ELECTRE, RSM-GA, and ANN-GA into the process parameter optimization of high-quality deep-drawn cylindrical copper cups
S.P. Sundar Singh Sivam, R. Rajendran, N. Harshavardhana
Mechanics Based Design of Structures and Machines (2022) Vol. 52, Iss. 1, pp. 498-522
Closed Access | Times Cited: 17
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