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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:

Specific heat capacity of molten salt-based nanofluids in solar thermal applications: A paradigm of two modern ensemble machine learning methods
Mehdi Jamei, Masoud Karbasi, Ismail Adewale Olumegbon, et al.
Journal of Molecular Liquids (2021) Vol. 335, pp. 116434-116434
Closed Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

Recent Advances in Machine Learning Research for Nanofluid-Based Heat Transfer in Renewable Energy System
Prabhakar Sharma, Zafar Said, Anurag Kumar, et al.
Energy & Fuels (2022) Vol. 36, Iss. 13, pp. 6626-6658
Closed Access | Times Cited: 242
Synthesis, stability, density, viscosity of ethylene glycol-based ternary hybrid nanofluids: Experimental investigations and model -prediction using modern machine learning techniques
Zafar Said, Neşe Keklikçioğlu Çakmak, Prabhakar Sharma, et al.
Powder Technology (2022) Vol. 400, pp. 117190-117190
Closed Access | Times Cited: 134
Application of novel framework based on ensemble boosted regression trees and Gaussian process regression in modelling thermal performance of small-scale Organic Rankine Cycle (ORC) using hybrid nanofluid
Zafar Said, Prabhakar Sharma, Arun Kumar Tiwari, et al.
Journal of Cleaner Production (2022) Vol. 360, pp. 132194-132194
Closed Access | Times Cited: 81
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: 68
Performance optimization of energy-efficient solar absorbers for thermal energy harvesting in modern industrial environments using a solar deep learning model
Ammar Armghan, J. Logeshwaran, S. Raja, et al.
Heliyon (2024) Vol. 10, Iss. 4, pp. e26371-e26371
Open Access | Times Cited: 26
Optimization of thermophysical properties of nanofluids using a hybrid procedure based on machine learning, multi-objective optimization, and multi-criteria decision-making
Tao Zhang, Anahita Manafi Khajeh Pasha, S. Mohammad Sajadi, et al.
Chemical Engineering Journal (2024) Vol. 485, pp. 150059-150059
Closed Access | Times Cited: 23
Experimental analysis of novel ionic liquid-MXene hybrid nanofluid's energy storage properties: Model-prediction using modern ensemble machine learning methods
Zafar Said, Prabhakar Sharma, Navid Aslfattahi, et al.
Journal of Energy Storage (2022) Vol. 52, pp. 104858-104858
Closed Access | Times Cited: 65
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
Improving the thermal efficiency of a solar flat plate collector using MWCNT-Fe3O4/water hybrid nanofluids and ensemble machine learning
Zafar Said, Prabhakar Sharma, L. Syam Sundar, et al.
Case Studies in Thermal Engineering (2022) Vol. 40, pp. 102448-102448
Open Access | Times Cited: 63
Application of a modern multi-level ensemble approach for the estimation of critical shear stress in cohesive sediment mixture
U. K. Singh, Mehdi Jamei, Masoud Karbasi, et al.
Journal of Hydrology (2022) Vol. 607, pp. 127549-127549
Closed Access | Times Cited: 53
Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach
Mehdi Jamei, Mumtaz Ali, Masoud Karbasi, et al.
Applied Energy (2022) Vol. 326, pp. 119925-119925
Closed Access | Times Cited: 50
Using Bayesian optimization and ensemble boosted regression trees for optimizing thermal performance of solar flat plate collector under thermosyphon condition employing MWCNT-Fe3O4/water hybrid nanofluids
Zafar Said, Prabhakar Sharma, L. Syam Sundar, et al.
Sustainable Energy Technologies and Assessments (2022) Vol. 53, pp. 102708-102708
Closed Access | Times Cited: 47
Sonication impact on thermal conductivity of f-MWCNT nanofluids using XGBoost and Gaussian process regression
Zafar Said, Prabhakar Sharma, Bhaskor Jyoti Bora, et al.
Journal of the Taiwan Institute of Chemical Engineers (2023) Vol. 145, pp. 104818-104818
Closed Access | Times Cited: 38
Optimized ANFIS models based on grid partitioning, subtractive clustering, and fuzzy C-means to precise prediction of thermophysical properties of hybrid nanofluids
Zhongwei Zhang, Mohammed Al‐Bahrani, Behrooz Ruhani, et al.
Chemical Engineering Journal (2023) Vol. 471, pp. 144362-144362
Closed Access | Times Cited: 35
Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process
Wongchai Anupong, Abolfazl Mehbodniya, Julian Webber, et al.
Journal of Water Reuse and Desalination (2023)
Open Access | Times Cited: 33
A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture
Mehdi Jamei, Mumtaz Ali, Masoud Karbasi, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105895-105895
Closed Access | Times Cited: 24
Advancing heat transfer modeling through machine learning: A focus on forced convection with nanoparticles
Seyed Hamed Godasiaei, Ali J. Chamkha
Numerical Heat Transfer Part A Applications (2024), pp. 1-23
Closed Access | Times Cited: 11
Enhancing Solar Energy Conversion Efficiency: Thermophysical Property Predicting of MXene/Graphene Hybrid Nanofluids via Bayesian-Optimized Artificial Neural Networks
Dheyaa J. Jasim, Husam Rajab, As’ad Alizadeh, et al.
Results in Engineering (2024) Vol. 24, pp. 102858-102858
Open Access | Times Cited: 11
Exploring novel heat transfer correlations: Machine learning insights for molten salt heat exchangers
Seyed Hamed Godasiaei, Ali J. Chamkha
Numerical Heat Transfer Part A Applications (2024), pp. 1-18
Closed Access | Times Cited: 9
Artificial neural network hyperparameters optimization for predicting the thermal conductivity of MXene/graphene nanofluids
Yunyan Shang, Karrar A. Hammoodi, As’ad Alizadeh, et al.
Journal of the Taiwan Institute of Chemical Engineers (2024) Vol. 164, pp. 105673-105673
Closed Access | Times Cited: 9
Artificial intelligence-assisted characterization and optimization of red mud-based nanofluids for high-efficiency direct solar thermal absorption
K. Praveen Kumar, Rohit S. Khedkar, Prabhakar Sharma, et al.
Case Studies in Thermal Engineering (2024) Vol. 54, pp. 104087-104087
Open Access | Times Cited: 8
Optimizing building energy performance predictions: A comparative study of artificial intelligence models
Omer A. Alawi, Haslinda Mohamed Kamar, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬
Journal of Building Engineering (2024) Vol. 88, pp. 109247-109247
Closed Access | Times Cited: 8
Estimating the density of hybrid nanofluids for thermal energy application: Application of non-parametric and evolutionary polynomial regression data-intelligent techniques
Mehdi Jamei, Masoud Karbasi, Mehdi Mosharaf‐Dehkordi, et al.
Measurement (2021) Vol. 189, pp. 110524-110524
Closed Access | Times Cited: 47
Development of wavelet-based Kalman Online Sequential Extreme Learning Machine optimized with Boruta-Random Forest for drought index forecasting
Mehdi Jamei, Iman Ahmadianfar, Masoud Karbasi, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 117, pp. 105545-105545
Closed Access | Times Cited: 37
Experimental study on the thermal properties of Al 2 O 3 ‐CuO /water hybrid nanofluids: Development of an artificial intelligence model
Hallera Basavarajappa Marulasiddeshi, Praveen Kumar Kanti, Mehdi Jamei, et al.
International Journal of Energy Research (2022) Vol. 46, Iss. 15, pp. 21066-21083
Open Access | Times Cited: 34
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