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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Statistical characterization of semi-supervised neural networks for fault detection and diagnosis of air handling units
Cheng Fan, Xuyuan Liu, Peng Xue, et al.
Energy and Buildings (2021) Vol. 234, pp. 110733-110733
Closed Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

A Review on Data Preprocessing Techniques Toward Efficient and Reliable Knowledge Discovery From Building Operational Data
Cheng Fan, Mei‐Ling Chen, Xinghua Wang, et al.
Frontiers in Energy Research (2021) Vol. 9
Open Access | Times Cited: 260
AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
Yassine Himeur, Mariam Elnour, Fodil Fadli, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 4929-5021
Open Access | Times Cited: 243
Interpretable machine learning for building energy management: A state-of-the-art review
Zhe Chen, Fu Xiao, Fangzhou Guo, et al.
Advances in Applied Energy (2023) Vol. 9, pp. 100123-100123
Open Access | Times Cited: 153
A review of computing-based automated fault detection and diagnosis of heating, ventilation and air conditioning systems
Jianli Chen, Liang Zhang, Yanfei Li, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 161, pp. 112395-112395
Open Access | Times Cited: 104
Interpretation of convolutional neural network-based building HVAC fault diagnosis model using improved layer-wise relevance propagation
Guannan Li, Luhan Wang, Limei Shen, et al.
Energy and Buildings (2023) Vol. 286, pp. 112949-112949
Closed Access | Times Cited: 43
Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion
Qi Zhong, Enguang Xu, Yan Shi, et al.
Mechanical Systems and Signal Processing (2023) Vol. 189, pp. 110093-110093
Closed Access | Times Cited: 41
An explainable one-dimensional convolutional neural networks based fault diagnosis method for building heating, ventilation and air conditioning systems
Guannan Li, Qing Yao, Cheng Fan, et al.
Building and Environment (2021) Vol. 203, pp. 108057-108057
Closed Access | Times Cited: 95
Transfer learning-based strategies for fault diagnosis in building energy systems
Jiangyan Liu, Qing Zhang, Xin Li, et al.
Energy and Buildings (2021) Vol. 250, pp. 111256-111256
Closed Access | Times Cited: 95
A study on semi-supervised learning in enhancing performance of AHU unseen fault detection with limited labeled data
Cheng Fan, Yichen Liu, Xuyuan Liu, et al.
Sustainable Cities and Society (2021) Vol. 70, pp. 102874-102874
Closed Access | Times Cited: 64
Comparative study on deep transfer learning strategies for cross-system and cross-operation-condition building energy systems fault diagnosis
Guannan Li, Liang Chen, Jiangyan Liu, et al.
Energy (2022) Vol. 263, pp. 125943-125943
Closed Access | Times Cited: 58
A novel image-based transfer learning framework for cross-domain HVAC fault diagnosis: From multi-source data integration to knowledge sharing strategies
Cheng Fan, Weilin He, Yichen Liu, et al.
Energy and Buildings (2022) Vol. 262, pp. 111995-111995
Closed Access | Times Cited: 57
One step forward for smart chemical process fault detection and diagnosis
Xiaotian Bi, Ruoshi Qin, Deyang Wu, et al.
Computers & Chemical Engineering (2022) Vol. 164, pp. 107884-107884
Closed Access | Times Cited: 54
Fault detection and diagnosis of the air handling unit via combining the feature sparse representation based dynamic SFA and the LSTM network
Hanyuan Zhang, Chengdong Li, Qinglai Wei, et al.
Energy and Buildings (2022) Vol. 269, pp. 112241-112241
Closed Access | Times Cited: 46
Digital Twin for Fault Detection and Diagnosis of Building Operations: A Systematic Review
Faeze Hodavand, Issa J. Ramaji, Naimeh Sadeghi
Buildings (2023) Vol. 13, Iss. 6, pp. 1426-1426
Open Access | Times Cited: 34
Semi-Supervised Machine Learning for Fault Detection and Diagnosis of a Rooftop Unit
Mohammed G. Albayati, Jalal Faraj, Amy E. Thompson, et al.
Big Data Mining and Analytics (2023) Vol. 6, Iss. 2, pp. 170-184
Open Access | Times Cited: 32
A novel building heat pump system semi-supervised fault detection and diagnosis method under small and imbalanced data
Jianxin Zhang, Yuanyi Xu, Huanxin Chen, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106316-106316
Closed Access | Times Cited: 24
Novel transformer-based self-supervised learning methods for improved HVAC fault diagnosis performance with limited labeled data
Cheng Fan, Yutian Lei, Yongjun Sun, et al.
Energy (2023) Vol. 278, pp. 127972-127972
Closed Access | Times Cited: 21
A holistic semi-supervised method for imbalanced fault diagnosis of rotational machinery with out-of-distribution samples
Zhangjun Wu, Renli Xu, Yuansheng Luo, et al.
Reliability Engineering & System Safety (2024) Vol. 250, pp. 110297-110297
Closed Access | Times Cited: 9
A novel global modelling strategy integrated dynamic kernel canonical variate analysis for the air handling unit fault detection via considering the two-directional dynamics
Hanyuan Zhang, Yuyu Zhang, Huanhuan Meng, et al.
Journal of Building Engineering (2024) Vol. 96, pp. 110402-110402
Closed Access | Times Cited: 8
A novel deep generative modeling-based data augmentation strategy for improving short-term building energy predictions
Cheng Fan, Meiling Chen, Rui Tang, et al.
Building Simulation (2021) Vol. 15, Iss. 2, pp. 197-211
Closed Access | Times Cited: 47
Consistency Regularization Auto-Encoder Network for Semi-Supervised Process Fault Diagnosis
Yao Ma, Hongbo Shi, Shuai Tan, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-15
Closed Access | Times Cited: 28
A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems
Iva Matetić, Ivan Štajduhar, Igor Wolf, et al.
Sensors (2022) Vol. 23, Iss. 1, pp. 1-1
Open Access | Times Cited: 27
Experimental study on performance assessments of HVAC cross-domain fault diagnosis methods oriented to incomplete data problems
Qiang Zhang, Zhe Tian, Yakai Lu, et al.
Building and Environment (2023) Vol. 236, pp. 110264-110264
Closed Access | Times Cited: 19
Data‐driven fault diagnosis approaches for industrial equipment: A review
Atma Sahu, Sanjay Kumar Palei, Aishwarya Mishra
Expert Systems (2023) Vol. 41, Iss. 2
Closed Access | Times Cited: 19
Leveraging graph convolutional networks for semi-supervised fault diagnosis of HVAC systems in data-scarce contexts
Cheng Fan, Yiwen Lin, Marco Savino Piscitelli, et al.
Building Simulation (2023) Vol. 16, Iss. 8, pp. 1499-1517
Closed Access | Times Cited: 19
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