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

и другие.

Energy Reports, Год журнала: 2025, Номер 13, С. 4586 - 4608

Опубликована: Апрель 15, 2025

Язык: 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

и другие.

Fuel, Год журнала: 2025, Номер 390, С. 134700 - 134700

Опубликована: Фев. 18, 2025

Язык: Английский

Процитировано

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

и другие.

Case Studies in Thermal Engineering, Год журнала: 2025, Номер unknown, С. 105748 - 105748

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

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

и другие.

Energy Reports, Год журнала: 2025, Номер 13, С. 2255 - 2268

Опубликована: Фев. 5, 2025

Язык: Английский

Процитировано

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

и другие.

Progress in Nuclear Energy, Год журнала: 2025, Номер 180, С. 105602 - 105602

Опубликована: Янв. 14, 2025

Язык: Английский

Процитировано

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

и другие.

Ocean Engineering, Год журнала: 2025, Номер 321, С. 120382 - 120382

Опубликована: Янв. 20, 2025

Язык: Английский

Процитировано

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

и другие.

International Journal of Computational Intelligence Systems, Год журнала: 2025, Номер 18(1)

Опубликована: Янв. 27, 2025

Язык: Английский

Процитировано

1

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

V. Chandralega,

M. Shanmugasundaram, David Stone

и другие.

Case Studies in Construction Materials, Год журнала: 2025, Номер unknown, С. e04367 - e04367

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

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

и другие.

Journal of Energy Storage, Год журнала: 2025, Номер 114, С. 115757 - 115757

Опубликована: Фев. 10, 2025

Язык: Английский

Процитировано

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

и другие.

Process Safety and Environmental Protection, Год журнала: 2025, Номер unknown, С. 106904 - 106904

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

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

Applied Sciences, Год журнала: 2025, Номер 15(7), С. 3758 - 3758

Опубликована: Март 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.

Язык: Английский

Процитировано

1