Bayesian Networks in Fault Diagnosis
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Cites background from "Bayesian Networks in Fault Diagnosi..."
...Bayesian networks (BNs) are important probabilistic directed acyclic graphical models that can effectively characterize and analyze uncertainty, which is a problem commonly encountered in real-world domains, and handle state space explosion problems [3]....
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Cites methods from "Bayesian Networks in Fault Diagnosi..."
...Consequently, both supervised and unsupervised learning approaches, such as principal components analysis [2], [3], artificial neural networks (ANN) [4], Bayes network [5], and regression trees [6] have been applied to manufacturing process optimization....
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References
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"Bayesian Networks in Fault Diagnosi..." refers background in this paper
...ject is fragment generated by instantiating the class [96]....
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"Bayesian Networks in Fault Diagnosi..." refers background in this paper
...In general, fault diagnosis approaches can be classified into three categories: model-based [1], [2], signal-based [3]–[5], and...
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2,026 citations
"Bayesian Networks in Fault Diagnosi..." refers background in this paper
...proach uses detected signals to diagnose possible abnormalities and faults by comparing detected signals with prior information of normal industrial systems [9]....
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