Pipeline damage identification in nuclear industry using a particle swarm optimization-enhanced machine learning approach DOI
Qi Jiang,

Wenzhong Qu,

Xiao Li

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 133, P. 108467 - 108467

Published: April 23, 2024

Language: Английский

Advanced controls on energy reliability, flexibility and occupant-centric control for smart and energy-efficient buildings DOI
Zhengxuan Liu, Xiang Zhang, Ying Sun

et al.

Energy and Buildings, Journal Year: 2023, Volume and Issue: 297, P. 113436 - 113436

Published: Aug. 9, 2023

Language: Английский

Citations

66
A review on enhancing energy efficiency and adaptability through system integration for smart buildings DOI

Um-e-Habiba,

Ijaz Ahmed, Mohammad Asif

et al.

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: 89, P. 109354 - 109354

Published: April 18, 2024

Language: Английский

Citations

32
An integrated framework for sustainable and efficient building maintenance operations aligning with climate change, SDGs, and emerging technology DOI Creative Commons
Ali Hauashdh, Sasitharan Nagapan, Junaidah Jailani

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 21, P. 101822 - 101822

Published: Jan. 26, 2024

Improving the operation and maintenance of buildings can significantly reduce carbon emissions, energy consumption, other environmental challenges while promoting sustainability. While existing literature offers various frameworks, they primarily focus on traditional building procedures overlook importance integrating sustainability, climate change, factors, emerging technologies. To address this gap, research has developed a comprehensive framework that caters to current needs, challenges, future priorities. The integrated for operations aligns with Sustainable Development Goals (SDGs), change mitigation adaptation, adoption technology, conservation, as well safety, resilience, effectiveness. development encompassed four phases: pre-development phases 1 2, phase 3, validation 4. During process, issues were identified, impacts assessed, strategies developed. serves roadmap these requirements in operations, making significant contributions all three dimensions sustainability: environmental, social, economic. In summary, study in-depth analysis issues, potential improvements benefits providing practical guide industry stakeholders contribution body knowledge.

Language: Английский

Citations

31
Advanced predictive maintenance and fault diagnosis strategy for enhanced HVAC efficiency in buildings DOI
Niima Es-sakali,

Zineb Zoubir,

Samir Idrissi Kaitouni

et al.

Applied Thermal Engineering, Journal Year: 2024, Volume and Issue: 254, P. 123910 - 123910

Published: July 9, 2024

Language: Английский

Citations

17
Anomaly Detection Using Convolutional Autoencoder with Residual Gated Recurrent Unit and Weak Supervision for Photovoltaic Thermal Heat Pump System DOI

Lemmon Patrick John,

Sungmin Yoon,

Jiteng Li

et al.

Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 111694 - 111694

Published: Jan. 1, 2025

Language: Английский

Citations

2
A comprehensive review of the applications of machine learning for HVAC DOI Creative Commons
Siyang Zhou, A.A. Shah, Puiki Leung

et al.

DeCarbon, Journal Year: 2023, Volume and Issue: 2, P. 100023 - 100023

Published: Sept. 1, 2023

Heating, ventilation and air-conditioning (HVAC) accounts for around 40% of the total building energy consumption. It has therefore become a major target reductions, in terms both usage CO2 emissions. In light progress intelligence technologies, traditional methods HVAC optimization, control, fault diagnosis will struggle to meet essential requirements such as efficiency, occupancy comfort reliable detection. Machine learning data science have great potential this regard, particularly with developments information technology sensor equipment, providing access large volumes high-quality data. There remains, however, number challenges before machine can gain widespread adoption industry. This review summarizes recent literature on system control Unlike other reviews, we provide comprehensive coverage applications, including factors considered. A brief overview its applications is provided, after which critically appraise optimization Finally, discussion limitations current research suggest future directions.

Language: Английский

Citations

41
How to improve the application potential of deep learning model in HVAC fault diagnosis: Based on pruning and interpretable deep learning method DOI
Yuan Gao, Shohei Miyata, Yasunori Akashi

et al.

Applied Energy, Journal Year: 2023, Volume and Issue: 348, P. 121591 - 121591

Published: July 20, 2023

Language: Английский

Citations

26
Novel transformer-based self-supervised learning methods for improved HVAC fault diagnosis performance with limited labeled data DOI
Cheng Fan, Yutian Lei, Yongjun Sun

et al.

Energy, Journal Year: 2023, Volume and Issue: 278, P. 127972 - 127972

Published: May 31, 2023

Language: Английский

Citations

23
Automated data mining framework for building energy conservation aided by generative pre-trained transformers (GPT) DOI
Chaobo Zhang, Jian Zhang, Yang Zhao

et al.

Energy and Buildings, Journal Year: 2024, Volume and Issue: 305, P. 113877 - 113877

Published: Jan. 2, 2024

Language: Английский

Citations

15
A novel global modelling strategy integrated dynamic kernel canonical variate analysis for the air handling unit fault detection via considering the two-directional dynamics DOI
Hanyuan Zhang, Yuyu Zhang, Huanhuan Meng

et al.

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: 96, P. 110402 - 110402

Published: Aug. 15, 2024

Language: Английский

Citations

13