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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:

Feasibility of ANFIS-PSO and ANFIS-GA Models in Predicting Thermophysical Properties of Al2O3-MWCNT/Oil Hybrid Nanofluid
Ibrahim M. Alarifi, Hoàng M. Nguyẽn, Ali Naderi, et al.
Materials (2019) Vol. 12, Iss. 21, pp. 3628-3628
Open Access | Times Cited: 99

Showing 26-50 of 99 citing articles:

Improved prediction of monthly streamflow in a mountainous region by Metaheuristic-Enhanced deep learning and machine learning models using hydroclimatic data
Rana Muhammad Adnan, Amin Mirboluki, Mojtaba Mehraein, et al.
Theoretical and Applied Climatology (2023) Vol. 155, Iss. 1, pp. 205-228
Closed Access | Times Cited: 17
On the Thermal Performance of a Fractal Microchannel Subjected to Water and Kerosene Carbon Nanotube Nanofluid
Zongjie Lyu, Farzad Pourfattah, Ali Akbar Abbasian Arani, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 45
Feasibility of least-square support vector machine in predicting the effects of shear rate on the rheological properties and pumping power of MWCNT–MgO/oil hybrid nanofluid based on experimental data
Amin Asadi, Ibrahim M. Alarifi, Hoàng M. Nguyẽn, et al.
Journal of Thermal Analysis and Calorimetry (2020) Vol. 143, Iss. 2, pp. 1439-1454
Closed Access | Times Cited: 43
On the Role of Nanofluids in Thermal-hydraulic Performance of Heat Exchangers—A Review
Salah Almurtaji, Naser Ali, Joao A. Teixeira, et al.
Nanomaterials (2020) Vol. 10, Iss. 4, pp. 734-734
Open Access | Times Cited: 43
Prediction of Nanofluid Temperature Inside the Cavity by Integration of Grid Partition Clustering Categorization of a Learning Structure with the Fuzzy System
Narjes Nabipour, Meisam Babanezhad, Ali Taghvaie Nakhjiri, et al.
ACS Omega (2020) Vol. 5, Iss. 7, pp. 3571-3578
Open Access | Times Cited: 41
Effects of ultrasonication time on stability, dynamic viscosity, and pumping power management of MWCNT-water nanofluid: an experimental study
Amin Asadi, Ibrahim M. Alarifi
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 41
Predictability evaluation of support vector regression methods for thermophysical properties, heat transfer performance, and pumping power estimation of MWCNT/ZnO–engine oil hybrid nanofluid
Amin Asadi, Ali Naderi, Ibrahim M. Alarifi
Engineering With Computers (2020) Vol. 37, Iss. 4, pp. 3813-3823
Closed Access | Times Cited: 39
Thermo-electro-rheological behaviour of vanadium electrolyte-based electrochemical graphene oxide nanofluid designed for redox flow battery
Sadegh Aberoumand, Peter Woodfield, Ge Shi, et al.
Journal of Molecular Liquids (2021) Vol. 338, pp. 116860-116860
Closed Access | Times Cited: 36
Comparative evaluation of deep learning and machine learning in modelling pan evaporation using limited inputs
Özgür Kişi, Amin Mirboluki, Sujay Raghavendra Naganna, et al.
Hydrological Sciences Journal (2022) Vol. 67, Iss. 9, pp. 1309-1327
Closed Access | Times Cited: 22
MLP and optimized FCM-ANFIS models proposed for inlet turbulent flow under ultrasonic vibration
Mohammad Mahdi Tafarroj, Amin Amiri Delouei, Ahmad Hajjar, et al.
Journal of Thermal Analysis and Calorimetry (2023) Vol. 148, Iss. 24, pp. 13995-14009
Closed Access | Times Cited: 14
Predicting thermal conductivity and dynamic viscosity of nanofluid by employment of Support Vector Machines: A review
Ayman Alfaleh, Nidhal Ben Khedher, Sayed M. Eldin, et al.
Energy Reports (2023) Vol. 10, pp. 1259-1267
Open Access | Times Cited: 13
On the heat transfer effectiveness and pumping power assessment of a diamond-water nanofluid based on thermophysical properties: An experimental study
Adel Alshayji, Amin Asadi, Ibrahim M. Alarifi
Powder Technology (2020) Vol. 373, pp. 397-410
Closed Access | Times Cited: 37
Model-free adaptive iterative learning control of melt pool width in wire arc additive manufacturing
Chunyang Xia, Zengxi Pan, Shiyu Zhang, et al.
The International Journal of Advanced Manufacturing Technology (2020) Vol. 110, Iss. 7-8, pp. 2131-2142
Closed Access | Times Cited: 36
Nanofluids thermal conductivity prediction applying a novel hybrid data-driven model validated using Monte Carlo-based sensitivity analysis
Ali Naseri, Mehdi Jamei, Iman Ahmadianfar, et al.
Engineering With Computers (2020) Vol. 38, Iss. S1, pp. 815-839
Closed Access | Times Cited: 33
A review on recent advances and applications of nanofluids in plate heat exchanger
Sanjeev Kumar Gupta, Shubham Gupta, Tushar Gupta, et al.
Materials Today Proceedings (2020) Vol. 44, pp. 229-241
Closed Access | Times Cited: 33
A Novel Optimization Algorithm: Cascaded Adaptive Neuro-Fuzzy Inference System
Namal Rathnayake, Tuan Linh Dang, Yukinobu Hoshino
International Journal of Fuzzy Systems (2021) Vol. 23, Iss. 7, pp. 1955-1971
Closed Access | Times Cited: 27
Improving the thermophysical properties of hybrid nanocellulose-copper (II) oxide (CNC-CuO) as a lubricant additives: A novel nanolubricant for tribology application
Mohd Kamal Kamarulzaman, Sakinah Hisham, K. Kadirgama, et al.
Fuel (2022) Vol. 332, pp. 126229-126229
Open Access | Times Cited: 19
Effect of use of MWCNT/oil nanofluid on the performance of solar organic Rankine cycle
Alireza Refiei, Reyhaneh Loni, Gholamhassan Najafi, et al.
Energy Reports (2020) Vol. 6, pp. 782-794
Open Access | Times Cited: 28
On the effects of nanomaterials on the performance of solar distillation systems-A comprehensive review
Ibrahim M. Alarifi, Ahmed G. Abo‐Khalil, Abdel‐Rahman Al‐Qawasmi, et al.
Solar Energy (2021) Vol. 218, pp. 596-610
Closed Access | Times Cited: 26
Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction
Humphrey Adun, Ifeoluwa Wole‐Osho, Eric C. Okonkwo, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 13, pp. 11233-11254
Open Access | Times Cited: 17
Power Management Strategy Based on Adaptive Neuro Fuzzy Inference System for AC Microgrid
Hesham M. Fekry, Azza A. ElDesouky, Ahmed M. Kassem, et al.
IEEE Access (2020) Vol. 8, pp. 192087-192100
Open Access | Times Cited: 26
Progress and application of nanofluids in solar collectors: An overview of recent advances
Sanjeev Kumar Gupta, Sangam Dixit
Materials Today Proceedings (2020) Vol. 44, pp. 250-259
Closed Access | Times Cited: 25
Utilization of Machine Learning Methods in Modeling Specific Heat Capacity of Nanofluids
Mamdouh El Haj Assad, Ibrahim Mahariq, Raymond Ghandour, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2021) Vol. 70, Iss. 1, pp. 361-374
Open Access | Times Cited: 18
Analysis of the Impact of Clustering Techniques and Parameters on Evolutionary-Based Hybrid Models for Forecasting Electricity Consumption
Stephen Oladipo, Yanxia Sun, Abraham Amole
IEEE Access (2023) Vol. 11, pp. 82838-82856
Open Access | Times Cited: 7
Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal
Fawzi Gougam, Chemseddine Rahmoune, Djamel Benazzouz, et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2020) Vol. 235, Iss. 20, pp. 5186-5197
Closed Access | Times Cited: 19

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