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	A novel adaptive fault detection methodology for complex system using deep belief networks and multiple models: A case study on cryogenic propellant loading system
	Ren, Hao[1]; Chai, Yi[1,2]; Qu, Jianfeng[1]; Ye, Xin[3]; Tang, Qiu[1]
	2018
卷号	275页码:2111-2125
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2973332
专题	重庆大学
推荐引用方式 GB/T 7714	Ren, Hao[1],Chai, Yi[1,2],Qu, Jianfeng[1],et al. A novel adaptive fault detection methodology for complex system using deep belief networks and multiple models: A case study on cryogenic propellant loading system[J],2018,275:2111-2125.
APA	Ren, Hao[1],Chai, Yi[1,2],Qu, Jianfeng[1],Ye, Xin[3],&Tang, Qiu[1].(2018).A novel adaptive fault detection methodology for complex system using deep belief networks and multiple models: A case study on cryogenic propellant loading system.,275,2111-2125.
MLA	Ren, Hao[1],et al."A novel adaptive fault detection methodology for complex system using deep belief networks and multiple models: A case study on cryogenic propellant loading system".275(2018):2111-2125.

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