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Journal article
A single Bayesian network classifier for monitoring with unknown classes
Engineering Applications of Artificial Intelligence, Vol.85, pp.681-690
85
2019
Web of Science ID: WOS:000488994300053
Abstract
In this paper, the Conditional Gaussian Networks (CGNs), a form of Bayesian Networks (BN), are used as a statistical process monitoring approach to detect and diagnose faults. The proposed approach improves the structure of Bayesian networks and generalizes a few results regarding statistical tests and the use of an exclusion criterion. The proposed framework is evaluated using data from the benchmark Tennessee Eastman Process (TEP) with various scenarios.
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Details
- Title
- A single Bayesian network classifier for monitoring with unknown classes
- Publication Details
- Engineering Applications of Artificial Intelligence, Vol.85, pp.681-690
- Resource Type
- Journal article
- Publisher
- Elsevier Ltd.; United Kingdom
- Series
- 85
- Copyright
- © 2019 Published by Elsevier Ltd.
- Identifiers
- WOS:000488994300053; 99380090782906600
- Academic Unit
- Mathematics and Statistics; Hal Marcus College of Science and Engineering
- Language
- English