Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing …

T Hai, A Basem, A Alizadeh, K Sharma, DJ Jasim… - Scientific Reports, 2024 - nature.com
Suspensions containing microencapsulated phase change materials (MPCMs) play a
crucial role in thermal energy storage (TES) systems and have applications in building …

Insights into water-lubricated transport of heavy and extra-heavy oils: Application of CFD, RSM, and metaheuristic optimized machine learning models

M Alsehli, A Basem, K Mausam, A Alshamrani… - Fuel, 2024 - Elsevier
With diminishing light crude oil reserves, the focus shifts to heavy and extra-heavy crude oil,
posing challenges with high viscosity impeding flow. Water-lubricated technology addresses …

Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable …

T Hai, A Basem, A Alizadeh, K Sharma, DJ Jasim… - Scientific Reports, 2024 - nature.com
Optimization of thermophysical properties (TPPs) of MXene-based nanofluids is essential to
increase the performance of hybrid solar photovoltaic and thermal (PV/T) systems. This …

Artificial neural network hyperparameters optimization for predicting the thermal conductivity of MXene/graphene nanofluids

Y Shang, KA Hammoodi, A Alizadeh, K Sharma… - Journal of the Taiwan …, 2024 - Elsevier
Background The critical role of thermal conductivity (TC) as a significant thermo-physical
property in MXene/graphene-based nanofluids for photovoltaic/thermal systems has …

[HTML][HTML] Enhancing solar energy conversion efficiency: Thermophysical property predicting of MXene/Graphene hybrid nanofluids via bayesian-optimized artificial …

H Rajab, A Alizadeh, K Sharma, M Ahmed… - Results in …, 2024 - Elsevier
Accurately predicting thermo-physical properties (TPPs) of MXene/graphene-based
nanofluids is crucial for photovoltaic/thermal solar systems, driving focused research on …

Optimizing ternary hybrid nanofluids using neural networks, gene expression programming, and multi-objective particle swarm optimization: a computational …

T Hai, A Basem, A Alizadeh, PK Singh, H Rajab… - Scientific Reports, 2025 - nature.com
The performance of nanofluids is largely determined by their thermophysical properties.
Optimizing these properties can significantly enhance nanofluid performance. This study …

Accurate prediction of the rheological behavior of MWCNT-Al2O3/water-ethylene glycol nanofluid with metaheuristic-optimized machine learning models

Y Ru, ABM Ali, KH Qader, HK Abdulaali, R Jhala… - International Journal of …, 2025 - Elsevier
The accurate prediction of the rheological properties of nanofluids is critical for optimizing
their application in various industrial systems. This study focuses on the dynamic viscosity …

Harnessing meta-heuristic, Bayesian, and search-based techniques in optimizing machine learning models for improved energy storage with microencapsulated …

LB Said, A Basem, AJ Sultan, PK Singh… - … Communications in Heat …, 2025 - Elsevier
In recent years, systems based on microencapsulated phase change materials (MPCMs)
have found applications in thermal energy storage, smart building construction, and battery …

A novel approach for optimizing a photovoltaic thermal system combined with solar thermal collector: Integrating RSM, multi-objective bat algorithm and VIKOR …

CY Hsu, H Pallathadka, P Patel, KS Yogi… - Journal of the Taiwan …, 2025 - Elsevier
Background A critical gap persists in solar technologies research regarding combining
response surface methodology (RSM) and the optimization capabilities of artificial …

[HTML][HTML] Synergizing Neural Networks with Multi-Objective Thermal Exchange Optimization and PROMETHEE Decision-Making to Improve PCM-based Photovoltaic …

Y Li, A Basem, A Alizadeh, PK Singh, S Dixit… - Case Studies in Thermal …, 2025 - Elsevier
This study addresses the integration of machine learning (ML) and artificial intelligence (AI)
for optimizing photovoltaic-thermal (PVT) systems. While ML modeling has become …