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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:

Anomaly Detection Based on Sensor Data in Petroleum Industry Applications
Luis Martí, Nayat Sánchez-Pi, José Manuel Molina, et al.
Sensors (2015) Vol. 15, Iss. 2, pp. 2774-2797
Open Access | Times Cited: 151

Showing 1-25 of 151 citing articles:

Time series forecasting of petroleum production using deep LSTM recurrent networks
Alaa Sagheer, Mostafa Kotb
Neurocomputing (2018) Vol. 323, pp. 203-213
Closed Access | Times Cited: 760
A Unifying Review of Deep and Shallow Anomaly Detection
Lukas Ruff, Jacob Kauffmann, Robert A. Vandermeulen, et al.
Proceedings of the IEEE (2021) Vol. 109, Iss. 5, pp. 756-795
Open Access | Times Cited: 685
Adversarially Learned Anomaly Detection
Houssam Zenati, Manon Romain, Chuan-Sheng Foo, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2018), pp. 727-736
Open Access | Times Cited: 343
LSTM-Based VAE-GAN for Time-Series Anomaly Detection
Zijian Niu, Ke Yu, Xiaofei Wu
Sensors (2020) Vol. 20, Iss. 13, pp. 3738-3738
Open Access | Times Cited: 150
Time-series anomaly detection with stacked Transformer representations and 1D convolutional network
Jina Kim, Hyeongwon Kang, Pilsung Kang
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105964-105964
Closed Access | Times Cited: 69
Transformer-based multivariate time series anomaly detection using inter-variable attention mechanism
Hyeongwon Kang, Pilsung Kang
Knowledge-Based Systems (2024) Vol. 290, pp. 111507-111507
Closed Access | Times Cited: 19
Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review
Zhibin Zhao, Jingyao Wu, Tianfu Li, et al.
Chinese Journal of Mechanical Engineering (2021) Vol. 34, Iss. 1
Open Access | Times Cited: 98
IoT Open-Source Architecture for the Maintenance of Building Facilities
Valentina Villa, Berardo Naticchia, Giulia Bruno, et al.
Applied Sciences (2021) Vol. 11, Iss. 12, pp. 5374-5374
Open Access | Times Cited: 84
Performance evaluation of outlier detection techniques in production timeseries: A systematic review and meta-analysis
Hamzeh Alimohammadi, Shengnan Nancy Chen
Expert Systems with Applications (2021) Vol. 191, pp. 116371-116371
Closed Access | Times Cited: 62
Advanced Intrusion Detection Combining Signature-Based and Behavior-Based Detection Methods
Hee-Yong Kwon, Taesic Kim, Mun‐Kyu Lee
Electronics (2022) Vol. 11, Iss. 6, pp. 867-867
Open Access | Times Cited: 39
Securing Industrial Control Systems: Components, Cyber Threats, and Machine Learning-Driven Defense Strategies
Mary Nankya, Robin Chataut, Robert Akl
Sensors (2023) Vol. 23, Iss. 21, pp. 8840-8840
Open Access | Times Cited: 27
A novel anomaly detection algorithm for sensor data under uncertainty
Raihan Ul Islam, Mohammad Shahadat Hossain, Karl Andersson
Soft Computing (2016) Vol. 22, Iss. 5, pp. 1623-1639
Open Access | Times Cited: 82
Anomaly detection for Smart City applications over 5G low power wide area networks
José Santos, Philip Leroux, Tim Wauters, et al.
NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium (2018), pp. 1-9
Open Access | Times Cited: 59
Anomaly Detection for Water Treatment System based on Neural Network with Automatic Architecture Optimization
Dmitry Shalyga, Pavel Filonov, Andrey Lavrentyev
arXiv (Cornell University) (2018)
Open Access | Times Cited: 59
Industrial Anomaly Detection: A Comparison of Unsupervised Neural Network Architectures
Barry Siegel
IEEE Sensors Letters (2020) Vol. 4, Iss. 8, pp. 1-4
Closed Access | Times Cited: 55
Anomaly Detection Based on Multidimensional Data Processing for Protecting Vital Devices in 6G-Enabled Massive IIoT
Guangjie Han, Juntao Tu, Li Liu, et al.
IEEE Internet of Things Journal (2021) Vol. 8, Iss. 7, pp. 5219-5229
Closed Access | Times Cited: 41
Hydrocarbon production dynamics forecasting using machine learning: A state-of-the-art review
Bin Liang, Jiang Liu, Junyu You, et al.
Fuel (2022) Vol. 337, pp. 127067-127067
Closed Access | Times Cited: 28
EST transformer: enhanced spatiotemporal representation learning for time series anomaly detection
Yao Gao, Rui Su, Xianye Ben, et al.
Journal of Intelligent Information Systems (2025)
Closed Access
Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network
Peng Jiang, Zhixin Hu, Jun Liu, et al.
Sensors (2016) Vol. 16, Iss. 10, pp. 1695-1695
Open Access | Times Cited: 53
Anomaly Detection in Manufacturing Systems Using Structured Neural Networks
Jie Liu, Jianlin Guo, Philip V. Orlik, et al.
(2018), pp. 175-180
Closed Access | Times Cited: 46
Metric Learning-Based Fault Diagnosis and Anomaly Detection for Industrial Data With Intraclass Variance
Keke Huang, Shujie Wu, Bei Sun, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 35, Iss. 1, pp. 547-558
Closed Access | Times Cited: 24
Using artificial intelligence to detect human errors in nuclear power plants: A case in operation and maintenance
Ezgi Gursel, Bhavya Reddy, Anahita Khojandi, et al.
Nuclear Engineering and Technology (2022) Vol. 55, Iss. 2, pp. 603-622
Open Access | Times Cited: 24
A self-supervised contrastive change point detection method for industrial time series
Xiangyu Bao, Liang Chen, Jingshu Zhong, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108217-108217
Closed Access | Times Cited: 4
A Multi-Scale Self-Supervision Approach for Bearing Anomaly Detection Using Sensor Data Under Multiple Operating Conditions
Zhuoheng Dai, Lei Jiang, Feifan Li, et al.
Sensors (2025) Vol. 25, Iss. 4, pp. 1185-1185
Open Access
An HMM-Based Anomaly Detection Approach for SCADA Systems
Kyriakos Stefanidis, Artemios G. Voyiatzis
Lecture notes in computer science (2016), pp. 85-99
Closed Access | Times Cited: 39
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