A deep belief network based fault diagnosis model for complex chemical processes

Computers & Chemical Engineering, pp. 395-407, 2017.

被引用36|引用|浏览48|DOI:https://doi.org/10.1016/j.compchemeng.2017.02.041
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其它链接dblp.uni-trier.de|academic.microsoft.com|www.sciencedirect.com

摘要

•An improved Deep Belief Network is proposed to extract fault features.•A new fault diagnosis model based on DBN is proved and applied.•An average fault diagnosis rate of 82.1% is achieved.

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