Ship motion extreme short time prediction of ship pitch based on diagonal recurrent neural network

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	Ship motion extreme short time prediction of ship pitch based on diagonal recurrent neural network
	Shen Yan 1; Xie Mei-ping 2
刊名	JOURNAL OF MARINE SCIENCE AND APPLICATION
	2005-06
卷号	4 期号:2 页码:56-60
关键词	extreme short time prediction diagonal recursive neural network recurrent prediction error learning algorithm unbiasedness
ISSN号	1671-9433
英文摘要	A DRNN (diagonal recurrent neural network) and its RPE (recurrent prediction error) learning algorithm are proposed in this paper. Using of the simple structure of DRNN can reduce the capacity of calculation. The principle of RPE learning algorithm is to adjust weights along the direction of Gauss-Newton. Meanwhile, it is unnecessary to calculate the second local derivative and the inverse matrixes, whose unbiasedness is proved. With application to the extremely short time prediction of large ship pitch, satisfactory results are obtained. Prediction effect of this algorithm is compared with that of auto-regression and periodical diagram method, and comparison results show that the proposed algorithm is feasible.
WOS研究方向	Engineering
语种	英语
出版者	HARBIN ENGINEERING UNIV
WOS记录号	WOS:000415494800010
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/2685]
专题	上海财经大学
通讯作者	Shen Yan
作者单位	1.Harbin Engn Univ, Sch Sci, Harbin 150001, Heilongjiang, Peoples R China; 2.Shanghai Univ Finance & Econ, Sch Informat Management & Engn, Shanghai 200433, Peoples R China
推荐引用方式 GB/T 7714	Shen Yan,Xie Mei-ping. Ship motion extreme short time prediction of ship pitch based on diagonal recurrent neural network[J]. JOURNAL OF MARINE SCIENCE AND APPLICATION,2005,4(2):56-60.
APA	Shen Yan,&Xie Mei-ping.(2005).Ship motion extreme short time prediction of ship pitch based on diagonal recurrent neural network.JOURNAL OF MARINE SCIENCE AND APPLICATION,4(2),56-60.
MLA	Shen Yan,et al."Ship motion extreme short time prediction of ship pitch based on diagonal recurrent neural network".JOURNAL OF MARINE SCIENCE AND APPLICATION 4.2(2005):56-60.