干旱区生态环境知识资源中心(Arid): Lake level dynamics exploration using deep learning, artificial neural network, and multiple linear regression techniques

Arid

DOI	10.1007/s12665-019-8210-7
	Lake level dynamics exploration using deep learning, artificial neural network, and multiple linear regression techniques
	Wen, Jinfeng 1; Han, Peng-Fei 1; Zhou, Zhangbing 1,2; Wang, Xu-Sheng 1
通讯作者	Han, Peng-Fei
来源期刊	ENVIRONMENTAL EARTH SCIENCES
ISSN	1866-6280
EISSN	1866-6299
出版年	2019
卷号	78 期号:6
英文摘要	Estimating the lake level dynamics accurately on a daily or finer timescale is important for a better understanding of ecosystems, especially the lakes in Badain Jaran Desert, China. In this study, lake level dynamics of Sumu Barun Jaran are simulated and predicted on a 2-h timescale using the deep learning (DL) model, which is structured for the first time in this area by considering critical environmental factors. Two machine learning methods, namely multiple linear regression (MLR) and the three-layered back-propagation artificial neural network (ANN), are also adopted for the prediction purpose. The performances of these models are evaluated by comparing the values of average relative error, the mean squared error, and the coefficient of determination. The result shows that the DL model performs better than MLR and ANN on these three criteria, and this DL model is beneficial for exploring the mechanism of lake level dynamics in Badain Jaran Desert.
英文关键词	Lake level Sumu Barun Jaran Badain Jaran Desert Deep learning Artificial neural network
类型	Article
语种	英语
国家	Peoples R China ; France
收录类别	SCI-E
WOS记录号	WOS:000461372900005
WOS关键词	PREDICTION ; MODEL ; FLUCTUATIONS ; PARAMETERS ; FUZZY
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/215402
作者单位	1.China Univ Geosci, Minist Educ, Key Lab Groundwater Circulat & Environm Evolut, Beijing 100083, Peoples R China; 2.TELECOM SudParis, Comp Sci Dept, F-91011 Evry, France
推荐引用方式 GB/T 7714	Wen, Jinfeng,Han, Peng-Fei,Zhou, Zhangbing,et al. Lake level dynamics exploration using deep learning, artificial neural network, and multiple linear regression techniques[J],2019,78(6).
APA	Wen, Jinfeng,Han, Peng-Fei,Zhou, Zhangbing,&Wang, Xu-Sheng.(2019).Lake level dynamics exploration using deep learning, artificial neural network, and multiple linear regression techniques.ENVIRONMENTAL EARTH SCIENCES,78(6).
MLA	Wen, Jinfeng,et al."Lake level dynamics exploration using deep learning, artificial neural network, and multiple linear regression techniques".ENVIRONMENTAL EARTH SCIENCES 78.6(2019).