LSTM Based Prediction and Time-Temperature Varying Rate Fusion for Hydropower Plant Anomaly Detection: A Case Study-Reference-Cited by-同舟云学术

LSTM Based Prediction and Time-Temperature Varying Rate Fusion for Hydropower Plant Anomaly Detection: A Case Study

Published:2018-12-15 Issue: Volume: Page:86-94
ISSN:1876-1100
Container-title:Advanced Manufacturing and Automation VIII
language:
Short-container-title:

Author:

Yuan Jin,Wang Yi,Wang Kesheng

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-13-2375-1_13

Reference10 articles.

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4. Wang, Y., Ma, H.-S., Yang, J.-H., Wang, K.-S.: Industry 4.0: a way from mass customization to mass personalization production. Adv. Manuf. 5(4), 311–320 (2017)

5. Bram, J., Ruud, T., Tiedo, T.: The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance. Reliab. Eng. Syst. Saf. 158, 21–30 (2017)

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