Supervised machine learning optimization of zeolite-based PVT systems with and without graphite for enhanced thermal output

A tutorial on Gaussian process regression: modelling, exploring, and exploiting functions

Schulz, E., Speekenbrink, M., & Krause, A. (2018) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2018.03.001 · Cited by 1,735 · see citing works

Prediction of energetic performance of a building integrated photovoltaic/thermal system thorough artificial neural network and hybrid particle swarm optimization models

Alnaqi, A. A., Moayedi, H., Shahsavar, A., & Nguyen, T. K. (2019) · Energy Conversion and Management · doi:10.1016/j.enconman.2019.01.005 · Cited by 132 · see citing works

A comprehensive review of photovoltaic-thermal (PVT) technology: Performance evaluation and contemporary development

Tiwari, A. K., Chatterjee, K., Agrawal, S., & Singh, G. K. (2023) · Energy Reports · doi:10.1016/j.egyr.2023.09.043 · Cited by 119 · see citing works

Developing GPR model for forecasting the rock fragmentation in surface mines

Gao, W. D., Karbasi, M., Hasanipanah, M., Zhang, X., & Guo, J. (2017) · Engineering With Computers · doi:10.1007/s00366-017-0544-8 · Cited by 100 · see citing works

Using artificial neural network models and particle swarm optimization for manner prediction of a photovoltaic thermal nanofluid based collector

Kalani, H., Sardarabadi, M., & Passandideh‐Fard, M. (2016) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2016.11.105 · Cited by 92 · see citing works

Energy and economic analysis of building integrated photovoltaic thermal system: Seasonal dynamic modeling assisted with machine learning-aided method and multi-objective genetic optimization

Shboul, B., Zayed, M. E., Ashraf, W. M., Usman, M., Roy, D., Irshad, K., & Rehman, S. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2024.03.049 · Cited by 89 · see citing works

Renewable energy sources integration via machine learning modelling: A systematic literature review

Alazemi, T., Darwish, M. M., & Radi, M. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26088 · Cited by 85 · see citing works

Enhancing photovoltaic thermal (PVT) performance with hybrid solar collector using phase change material, porous media, and nanofluid

Mahdi, Z. M., Al-Shamani, A. N., Al‐Manea, A., Al-Zurfi, H. A., Al-Rbaihat, R., Sopian, K., & Alahmer, A. I. (2024) · Solar Energy · doi:10.1016/j.solener.2024.112983 · Cited by 84 · see citing works

Innovations in improving photovoltaic efficiency: A review of performance enhancement techniques

Abdel‐Aziz, M. M., & ElBahloul, A. A. (2025) · Energy Conversion and Management · doi:10.1016/j.enconman.2025.119589 · Cited by 77 · see citing works

A systematic review on predicting PV system parameters using machine learning

Jobayer, M., Hasan, M. R., Rashid, M. N., & Hasan, M. R. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e16815 · Cited by 65 · see citing works

Influence of non-ideal gas characteristics on working fluid properties and thermal cycle of space nuclear power generation system

Xu, C., Kong, F., Yu, D., Yu, J., & Khan, M. S. (2021) · Energy · doi:10.1016/j.energy.2021.119881 · Cited by 63 · see citing works

The contribution of artificial intelligence to phase change materials in thermal energy storage: From prediction to optimization

Liu, S., Han, J., Shen, Y., Khan, S. Y., Ji, W., Jin, H., & Kumar, M. (2024) · Renewable Energy · doi:10.1016/j.renene.2024.121973 · Cited by 52 · see citing works

A numerical investigation on improving the thermal efficiency of PV panels through integration with solar water collectors

Abdel‐Aziz, M. M., Kabeel, A. E., Khelifa, A., Attia, M. E. H., & Bady, M. (2025) · Solar Energy · doi:10.1016/j.solener.2025.113259 · Cited by 52 · see citing works

Prediction and evaluation of photovoltaic-thermal energy systems production using artificial neural network and experimental dataset

Yousif, J. H., & Kazem, H. A. (2021) · Case Studies in Thermal Engineering · doi:10.1016/j.csite.2021.101297 · Cited by 49 · see citing works

Phase change materials in solar energy storage: Recent progress, environmental impact, challenges, and perspectives

Hamzat, A. K., Pasanaje, A. H., Omisanya, M. I., Şahin, A. Z., Maselugbo, A. O., Adediran, I. A., Mudashiru, L. O., Asmatulu, E., Oyetunji, O. R., & Asmatulu, R. (2025) · Journal of Energy Storage · doi:10.1016/j.est.2025.115762 · Cited by 49 · see citing works

Enhancing the performance of a photovoltaic thermal system with phase change materials: Predictive modelling and evaluation using neural networks

Deka, M. J., Kamble, A. D., Das, D., Sharma, P., Ali, S., Kalita, P., Bora, B. J., & Kalita, P. (2024) · Renewable Energy · doi:10.1016/j.renene.2024.120091 · Cited by 45 · see citing works

Improving Photovoltaic Power Prediction: Insights through Computational Modeling and Feature Selection

Amiri, A. F., Chouder, A., Oudira, H., Silvestre, S., & Kichou, S. (2024) · Energies · doi:10.3390/en17133078 · Cited by 35 · see citing works

Enhancing the Performance of Photovoltaic Solar Cells Using a Hybrid Cooling Technique of Thermoelectric Generator and Heat Sink

Hachim, D. M., Al‐Manea, A., Al-Rbaihat, R., Abed, Q. A., Sadiq, M., Homod, R. Z., & Alahmer, A. I. (2024) · Journal of Solar Energy Engineering · doi:10.1115/1.4066842 · Cited by 35 · see citing works

Optimal air cooling gap width at the top of the PVT: thermal and electrical efficiency analysis

Attia, M. E. H., Kabeel, A. E., Khelifa, A., Abdel‐Aziz, M. M., Sathyamurthy, R., & El-Maghlany, W. M. (2025) · Journal of Thermal Analysis and Calorimetry · doi:10.1007/s10973-024-13882-2 · Cited by 35 · see citing works

Conceptual design and optimization of power generation system for lead-based reactor

Khan, M. S., Bai, Y., Huang, Q., Xu, C., Sun, L., Zou, X., & Wang, L. (2019) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2019.114714 · Cited by 29 · see citing works

Optimization of different composite sorption materials and their thickness for enhanced PV cooling performance: A multiphysics simulation approach

Abdel‐Aziz, M. M., & ElBahloul, A. A. (2025) · Solar Energy Materials and Solar Cells · doi:10.1016/j.solmat.2025.113554 · Cited by 28 · see citing works

Comparative assessment of thermal oils and water as working fluids in parabolic trough collectors for enhanced solar power generation

Jabbar, H. A., Alwan, K. J., Hachim, D. M., Al‐Manea, A., Al-Rbaihat, R., & Alahmer, A. I. (2024) · Engineering Research Express · doi:10.1088/2631-8695/ad6122 · Cited by 27 · see citing works

Energy, exergy, and economical analyses of a photovoltaic thermal system integrated with the natural zeolites for heat management

Kandilli, C. (2019) · International Journal of Energy Research · doi:10.1002/er.4605 · Cited by 26 · see citing works

Optimizing solar panel performance with new algorithm incorporating duct with helical tape and hybrid nanofluid

Anisi, A., Sheikholeslami, M., Khalili, Z., & Boora, F. M. (2024) · Journal of the Taiwan Institute of Chemical Engineers · doi:10.1016/j.jtice.2024.105908 · Cited by 25 · see citing works

Analysis of hidden nodes for multi-layer perceptron neural networks

Jou, I.-C., You, S.-S., & Chang, L.-W. (1994) · Pattern Recognition · doi:10.1016/0031-3203(94)90170-8 · Cited by 23 · see citing works

Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems

Yongxin, L., Basem, A., Alizadeh, A., Singh, P. K., Dixit, S., Abdulaali, H. K., Ali, R., Cajla, P., Rajab, H., & Ghachem, K. (2025) · Case Studies in Thermal Engineering · doi:10.1016/j.csite.2025.105851 · Cited by 22 · see citing works

RBFNN-Based Adaptive Integral Sliding Mode Feedback and Feedforward Control for a Lower Limb Exoskeleton Robot

Yuan, T., Zhang, C., Feng, Y., Lv, P., Zhang, M., & Li, S. (2024) · Electronics · doi:10.3390/electronics13061043 · Cited by 20 · see citing works

Feature perturbation augmentation for reliable evaluation of importance estimators in neural networks

Brocki, L., & Chung, N. C. (2023) · Pattern Recognition Letters · doi:10.1016/j.patrec.2023.10.012 · Cited by 16 · see citing works

Numerical analysis and deep learning algorithm for photovoltaic-thermal systems using various nanofluids and volume fractions at Riyadh, Saudi Arabia

Alhamayani, A. D. (2024) · Case Studies in Thermal Engineering · doi:10.1016/j.csite.2024.103974 · Cited by 16 · see citing works

Machine learning assisted calibration of PVT simulations for SiC crystal growth

Taucher, L., Ramadan, Z., Hammer, R., Obermüller, T., Auer, P., & Romaner, L. (2024) · CrystEngComm · doi:10.1039/d4ce00866a · Cited by 14 · see citing works

Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different Nanofluids

Singh, M., Solanki, S. C., Agrawal, B., & Bhargava, R. (2024) · International Journal of Photoenergy · doi:10.1155/2024/6649100 · Cited by 14 · see citing works

Investigation of thermophysical properties of natural zeolite plates enhanced with graphite powder for thermal management of PV thermal systems

Kandilli, C., Acikbas, Y., & Uzel, M. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.128558 · Cited by 14 · see citing works

Prediction of the effect of temperature on electric power in photovoltaic thermal systems based on natural zeolite plates

Metlek, S., Kandilli, C., & Kayaalp, K. (2021) · International Journal of Energy Research · doi:10.1002/er.7575 · Cited by 11 · see citing works

An artificial intelligence approach to predict energy parameters in a photovoltaic-thermal system within a greenhouse

Shojapour, S., Motevali, A., Samadi, S. H., Ranjbar-Nedamani, A., Biparva, P., & Anvari‐Moghaddam, A. (2025) · Solar Energy · doi:10.1016/j.solener.2025.113544 · Cited by 10 · see citing works

Development of an optimum flow rate control method for a hybrid system with PVT and heat pump using a clustering-based regression model

Chae, S., Jeong, S., & Nam, Y. (2025) · Renewable Energy · doi:10.1016/j.renene.2025.123619 · Cited by 9 · see citing works

Levenberg–Marquardt back-propagation algorithm for a developing unsteady hybrid nanofluid mixed convective flow across a revolving sphere: irreversibility analysis

Chakraborty, A., Janapatla, P., & Chatterjee, B. (2024) · The European Physical Journal Plus · doi:10.1140/epjp/s13360-024-05867-9 · Cited by 5 · see citing works

An online learning method for assessing smart grid stability under dynamic perturbations

Alaerjan, A., & Jabeur, R. (2025) · Scientific Reports · doi:10.1038/s41598-025-94718-3 · Cited by 5 · see citing works

Design and Implementation Accurate Three Distance Sensors Device Using Neural Network

Khaleel, H. Z., & Raheem, F. A. (2024) · Tikrit Journal of Engineering Sciences · doi:10.25130/tjes.31.2.13 · Cited by 3 · see citing works

System-level exergo-hydraulic optimization and dynamic modeling of a Geo-Aero-Voltaic bifluid collector with dual thermal loops

Baklouti, I., Mujeebu, M. A., & Noor, M. M. (2026) · Energy · doi:10.1016/j.energy.2026.142562

Prediction of the effect of temperature on electric power in photovoltaic thermal systems based on natural zeolite plates

Metlek, S., Kandilli, C., & Kayaalp, K. (2021) · International Journal of Energy Research · doi:10.1002/er.7575 · Cited by 11 · see citing works

Optimisation design and operation parameters of a photovoltaic thermal system integrated with natural zeolite

Kandilli, C., & Mertoglu, B. (2020) · International Journal of Hydromechatronics · doi:10.1504/ijhm.2020.10029840 · Cited by 24 · see citing works

Optimization and Performance Prediction of an Air‐Based PVT System Using Machine Learning

Minh, N. V., Haggam, R. A., Hamida, M. B. B., Abdallah, A. S. H., Purushothaman, S., Srimanickam, B., & Sampath, S. (2026) · Chemical Engineering & Technology · doi:10.1002/ceat.70290

AI-integrated design of nanofluid-based PVT systems containing nano-enhanced PCM: Combining optimized GPR models with grasshopper optimization and the CoCoSo algorithm

Khan, R., Mohsen, A. M., Alizadeh, A., Singh-Sawaran-Singh, N., Hussein, S. A., Sadeq, A. M., Rajab, H., & Hajlaoui, K. (2025) · Case Studies in Thermal Engineering · doi:10.1016/j.csite.2025.107081 · Cited by 10 · see citing works

Dynamic modeling of photovoltaic–thermal systems using polynomial regression

Moradi, K., Jafari, F., Moghaddam, F., & Shafiee, Q. (2025) · Renewable Energy · doi:10.1016/j.renene.2025.123242 · Cited by 13 · see citing works