Deeppipe: an unsupervised model for abnormal condition detection of multi-product pipelines
Author:
Affiliation:
1. China University of Petroleum-Beijing,Beijing,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10023546/10022325/10023584.pdf?arnumber=10023584
Reference19 articles.
1. Minor class-based status detection for pipeline network using enhanced generative adversarial networks
2. Deeppipe: a customized generative model for estimations of liquid pipeline leakage parameters
3. An online real-time estimation tool of leakage parameters for hazardous liquid pipelines
4. Deeppipe: A hybrid model for multi-product pipeline condition recognition based on process and data coupling
5. Status detection from spatial-temporal data in pipeline network using data transformation convolutional neural network
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