Carbon neutrality and economic stability nexus: An integrated renewable energy transition to decarbonize the energy sector DOI
Muhammad Amir Raza, M.M. Aman, Laveet Kumar

et al.

Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 4586 - 4608

Published: April 15, 2025

Language: Английский

A data-driven multi-criteria optimization of a biogas-fed s-graz cycle combined with biogas steam reforming and Claude cycle for sustainable hydrogen liquefaction DOI

Milad Feili,

Maghsoud Abdollahi Haghghi, Hadi Ghaebi

et al.

Fuel, Journal Year: 2025, Volume and Issue: 390, P. 134700 - 134700

Published: Feb. 18, 2025

Language: Английский

Citations

7
Heat Re-process Approach and Thermally Integrated Renewable Energy System for Power, Compressed Hydrogen, and Freshwater Production; ANN boosted Optimization and Techno-Enviro-Economic Analysis DOI Creative Commons
Zhaoyang Zuo,

J. Wang,

Mohammed A. Alghassab

et al.

Case Studies in Thermal Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105748 - 105748

Published: Jan. 1, 2025

Language: Английский

Citations

3
Optimal selection of CSP site for desalination system using GIS and AHP method in Hormozgan province, Iran DOI

Fateme Rasaei,

Hossein Yousefi,

Marziyeh Razeghi

et al.

Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 2255 - 2268

Published: Feb. 5, 2025

Language: Английский

Citations

2
Numerical modeling, comprehensive energy-exergy-environmental (3E) analysis, and efficiency-based enhancement of the secondary circuit of the marine propulsion system: A case study of NS Savannah DOI
Navid Delgarm,

Mahmoud Rostami Varnousfaaderani,

Hamid Farrokhfal

et al.

Progress in Nuclear Energy, Journal Year: 2025, Volume and Issue: 180, P. 105602 - 105602

Published: Jan. 14, 2025

Language: Английский

Citations

1
Prediction of maximum dynamic shear modulus of undisturbed marine soils in the eastern coast of China based on machine learning methods DOI
Yiliang Tu, Qianglong Yao,

Ying Zhou

et al.

Ocean Engineering, Journal Year: 2025, Volume and Issue: 321, P. 120382 - 120382

Published: Jan. 20, 2025

Language: Английский

Citations

1
Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan Island DOI Creative Commons
Heidar Ali Talebi, Javad Nikoukar, Majid Gandomkar

et al.

International Journal of Computational Intelligence Systems, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 27, 2025

Language: Английский

Citations

1
ENHANCING THE PERFORMANCE OF IRON-BASED BINDERS WITH SEAWATER AND CO2 SEQUESTRATION DOI Creative Commons

V. Chandralega,

M. Shanmugasundaram, David Stone

et al.

Case Studies in Construction Materials, Journal Year: 2025, Volume and Issue: unknown, P. e04367 - e04367

Published: Feb. 1, 2025

Language: Английский

Citations

1
Enhancing charging and discharging performance in a novel latent heat storage via design optimization and artificial neural network modeling DOI
Kourosh Vaferi, Amirhamzeh Farajollahi,

Towhid Gholizadeh

et al.

Journal of Energy Storage, Journal Year: 2025, Volume and Issue: 114, P. 115757 - 115757

Published: Feb. 10, 2025

Language: Английский

Citations

1
Integrating an innovative geothermal-driven multigeneration approach and LNG cold energy utilization process for sustainable energy supply, producing hydrogen, power, heating, and cooling DOI

Jing You,

Rui Xiao, Majed A. Alotaibi

et al.

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown, P. 106904 - 106904

Published: Feb. 1, 2025

Language: Английский

Citations

1
A Comprehensive Review of Machine Learning Models for Optimizing Wind Power Processes DOI Creative Commons
Cosmina-Mihaela Roșca, Adrian Stancu

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(7), P. 3758 - 3758

Published: March 29, 2025

Wind energy represents a solution for reducing environmental impact. For this reason, research studies the elements that propose optimizing wind production through intelligent solutions. Although there are address optimization of turbine performance or other indirectly related factors in production, remains topic insufficiently explored and synthesized literature. This how machine learning (ML) techniques can be applied to optimize production. aims study systematic applications ML identify analyze key stages optimized Through research, case highlighted by which methods proposed directly target issue power process turbines. From total 1049 articles obtained from Web Science database, most studied models context artificial neural networks, with 478 papers identified. Additionally, literature identifies 224 have random forest 114 incorporated gradient boosting about power. Among these, 60 specifically addressed aspect allows identification gaps The notes previous focused on forecasting, fault detection, efficiency. existing addresses indirect component performance. Thus, paper current discusses algorithms processes, future directions increasing efficiency turbines integrated predictive methods.

Language: Английский

Citations

1