Predictive maintenance based on anomaly detection using deep learning for air production unit in the railway industry-Reference-Cited by-同舟云学术

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Predictive maintenance based on anomaly detection using deep learning for air production unit in the railway industry

Published:2021-10-06 Issue: Volume: Page:
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Container-title:2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)
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Author:

Davari Narjes,Veloso Bruno,Ribeiro Rita P.,Pereira Pedro Mota,Gama Joao

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9564091/9564109/09564181.pdf?arnumber=9564181

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Anomaly-based error and intrusion detection in tabular data: No DNN outperforms tree-based classifiers;Future Generation Computer Systems;2024-11

2. From fault detection to anomaly explanation: A case study on predictive maintenance;Journal of Web Semantics;2024-07

3. Digital Sensor Forecasting for Metro Air Units: A Vector Autoregression Approach;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

4. Detecting and Explaining Anomalies in the Air Production Unit of a Train;Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing;2024-04-08

5. Enhancing Predictive Maintenance in Water Treatment Plants through Sparse Autoencoder Based Anomaly Detection;Journal of Machine and Computing;2024-04-05

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