Reducing neural network complexity via optimization algorithms for fault diagnosis in renewable energy systems DOI Creative Commons
Mansour Hajji, Amal Hichri, Zahra Yahyaoui

et al.

Ain Shams Engineering Journal, Journal Year: 2024, Volume and Issue: unknown, P. 103086 - 103086

Published: Oct. 1, 2024

Language: Английский

Exploring hydrogen geologic storage in China for future energy: Opportunities and challenges DOI

Zhengyang Du,

Zhenxue Dai, Zhijie Yang

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 196, P. 114366 - 114366

Published: March 15, 2024

Language: Английский

Citations

21
Analysis of the Impact of Information and Communication Technology, Digitalization, Renewable Energy and Financial Development on Environmental Sustainability DOI Creative Commons
Lanouar Charfeddine, Bilal Hussain, Montassar Kahia

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 201, P. 114609 - 114609

Published: June 10, 2024

Language: Английский

Citations

17
Financial leasing and China’s renewable energy firms' investment behavior: In the context of government subsidy reduction DOI
Yongjing Xie, Boqiang Lin

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 214, P. 115547 - 115547

Published: Feb. 28, 2025

Language: Английский

Citations

2
Analysis and review on air-cooled open cathode proton exchange membrane fuel cells: Bibliometric, environmental adaptation and prospect DOI
Chen Zhao, Fei Wang, Xiaoyu Wu

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 197, P. 114408 - 114408

Published: April 3, 2024

Language: Английский

Citations

7
Building Information Modeling and AI Algorithms for Optimizing Energy Performance in Hot Climates: A Comparative Study of Riyadh and Dubai DOI Creative Commons
Mohammad H. Mehraban,

Aljawharah A. Alnaser,

Samad M. E. Sepasgozar

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(9), P. 2748 - 2748

Published: Sept. 2, 2024

In response to increasing global temperatures and energy demands, optimizing buildings’ efficiency, particularly in hot climates, is an urgent challenge. While current research often relies on conventional estimation methods, there has been a decrease the efforts dedicated leveraging AI-based methodologies as technology advances. This implies dearth of multiparameter examinations AI-driven extreme case studies. For this reason, study aimed enhance performance residential buildings climates Dubai Riyadh by integrating Building Information Modeling (BIM) Machine Learning (ML). Detailed BIM models typical villa these regions were created using Revit, incorporating conventional, modern, green building envelopes (BEs). These served basis for simulations conducted with Green Studio (GBS) Insight, focusing crucial features such floor area, external internal walls, windows, flooring, roofing, orientation, infiltration, daylighting, more. To predict Energy Use Intensity (EUI), four ML algorithms, namely, Gradient Boosting (GBM), Random Forest (RF), Support Vector (SVM), Lasso Regression (LR), employed. GBM consistently outperformed others, demonstrating superior prediction accuracy R2 0.989. indicates that model explains 99% variance EUI, highlighting its effectiveness capturing relationships between consumption. Feature importance analysis (FIA) revealed roofs (29% scenarios (DS) 40% (RS)), walls (19% DS 29% RS), windows (15% 9% RS) have most impact Additionally, explored potential optimization, cavity RS double brick VIP insulation DS. The findings paper should be interpreted light certain limitations but they underscore combining sustainable design, offering actionable insights enhancing efficiency climates.

Language: Английский

Citations

6
Forecasting solar energy generation in the mediterranean region up to 2030–2050 using convolutional neural networks (CNN) DOI Creative Commons
Mahmood Abdoos,

Halimeh Rashidi,

Parastoo Esmaeili

et al.

Cleaner Energy Systems, Journal Year: 2024, Volume and Issue: 10, P. 100167 - 100167

Published: Dec. 10, 2024

Language: Английский

Citations

6
An efficient, compact, wide-angle, wide-band, and polarization-insensitive metamaterial electromagnetic energy harvester DOI Creative Commons
Najeeb Ullah, Md. Shabiul Islam, Ahasanul Hoque

et al.

Alexandria Engineering Journal, Journal Year: 2023, Volume and Issue: 82, P. 377 - 388

Published: Oct. 15, 2023

This paper introduces a metamaterial energy harvester that is compact, highly efficient, and capable of operating at wide angles. The proposed design has an outer ring resonator housing inverted T-shaped resonators, it can operate two distinct frequencies, 3.2 GHz 5.4 GHz. structure's impedance carefully designed to align with free space, ensuring efficient capture incident electromagnetic power minimal reflection. enables the resistor load receive in most manner. Based on simulation findings, exhibits notably higher conversion efficiency around 97 %. To ensure accuracy reliability outcomes, we fabricated 3x3 cell array conducted experimental tests within anechoic chamber. results exhibit strong correlation. Existing metamaterial-based harvesting designs frequently confront size, absorption band, polarization sensitivity limitations. Our compact distinguished by its ability accomplish near-unity greater efficiencies desired frequency bands. makes ideal option for systems wireless sensor networks prioritizing size.

Language: Английский

Citations

16
Disparity and driving forces of energy consumption in China's provincial urban residential sector under the carbon neutrality target DOI

Yilong Xiao,

Teng Ma,

Yan Ru Fang

et al.

Energy, Journal Year: 2024, Volume and Issue: 301, P. 131642 - 131642

Published: May 12, 2024

Language: Английский

Citations

5
Energy-saving benefits of thermal insulation and glazing in code-compliant office building in cooling-dominated climates DOI
M. Abdul Mujeebu, Noman Ashraf

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 199, P. 114532 - 114532

Published: May 17, 2024

Language: Английский

Citations

5
AI-Driven Building Redesign for Energy Efficiency and Cost Reduction DOI
Ahmed Emam

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 467 - 482

Published: March 13, 2025

Artificial intelligence (AI) and machine learning (ML) transform building design by optimizing energy consumption reducing costs. These technologies, integrated with Building Information Modeling (BIM) platforms like Revit, enable precise predictions, real-time optimization, renewable integration, achieving notable savings, such as up to 37% in HVAC systems. This review explores methodologies for applying AI design, including data extraction, simulation, validation using tools Autodesk Insight 360. It addresses challenges availability ethical concerns while highlighting AI's potential enhance efficiency sustainability. Future research suggests developing hybrid models, incorporating cognitive principles, leveraging emerging technologies IoT blockchain advance sustainable practices redefine processes.

Language: Английский

Citations

0