气候变化领域集成服务门户(CCPortal): Downscaling rainfall using deep learning long short-term memory and feedforward neural network

CCPortal

DOI	10.1002/joc.6066
	Downscaling rainfall using deep learning long short-term memory and feedforward neural network
	Duong Tran Anh; Van, Song P.; Dang, Thanh D.; Hoang, Long P.
发表日期	2019-08-01
ISSN	0899-8418
EISSN	1097-0088
卷号	39 期号:10 页码:4170-4188
英文摘要	Choosing downscaling techniques is crucial in obtaining accurate and reliable climate change predictions, allowing for detailed impact assessments of climate change at regional and local scales. Traditional statistical methods are likely inefficient in do
关键词	extreme indices FNN LSTM rainfall downscaling Vietnamese Mekong Delta
学科领域	Meteorology & Atmospheric Sciences
语种	英语
WOS记录号	WOS:000479031900019
来源期刊	INTERNATIONAL JOURNAL OF CLIMATOLOGY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/82213
作者单位	Tech Univ Munich, Inst Hydraul & Water Resources Engn, Arcisstr 21, D-80333 Munich, Germany
推荐引用方式 GB/T 7714	Duong Tran Anh,Van, Song P.,Dang, Thanh D.,et al. Downscaling rainfall using deep learning long short-term memory and feedforward neural network[J],2019,39(10):4170-4188.
APA	Duong Tran Anh,Van, Song P.,Dang, Thanh D.,&Hoang, Long P..(2019).Downscaling rainfall using deep learning long short-term memory and feedforward neural network.INTERNATIONAL JOURNAL OF CLIMATOLOGY,39(10),4170-4188.
MLA	Duong Tran Anh,et al."Downscaling rainfall using deep learning long short-term memory and feedforward neural network".INTERNATIONAL JOURNAL OF CLIMATOLOGY 39.10(2019):4170-4188.