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TD-LSTM: Temporal dependence-based LSTM networks for marine temperature prediction
Liu J(刘军)1,2; Zhang, Tong1; Han, Guangjie3; Gou, Yu1
Department机器人学研究室
Source PublicationSensors (Switzerland)
ISSN1424-8220
2018
Volume18Issue:11Pages:1-13
Indexed BySCI ; EI
EI Accession number20184606072266
WOS IDWOS:000451598900207
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; State Key Laboratory of Robotics ; National Natural Science Foundation of China-Guangdong Joint Fund ; program for Liaoning Excellent Talents in University
KeywordLong Short-term Memory (Lstm) Temporal Dependence Sea Surface Temperature (Sst) Prediction
Abstract

Changes in ocean temperature over time have important implications for marine ecosystems and global climate change. Marine temperature changes with time and has the features of closeness, period, and trend. This paper analyzes the temporal dependence of marine temperature variation at multiple depths and proposes a new ocean-temperature time-series prediction method based on the temporal dependence parameter matrix fusion of historical observation data. The Temporal Dependence-Based Long Short-Term Memory (LSTM) Networks for Marine Temperature Prediction (TD-LSTM) proves better than other methods while predicting sea-surface temperature (SST) by using Argo data. The performances were good at various depths and different regions.

Language英语
WOS SubjectChemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation
WOS KeywordFORECASTS ; SST
WOS Research AreaChemistry ; Electrochemistry ; Instruments & Instrumentation
Funding ProjectNational Natural Science Foundation of China[61631008] ; National Natural Science Foundation of China[61572172] ; National Natural Science Foundation of China[61872124] ; Fundamental Research Funds for the Central Universities[2017TD-18] ; Fundamental Research Funds for the Central Universities[DUT17RC(3)094] ; State Key Laboratory of Robotics[2015-O06] ; National Natural Science Foundation of China-Guangdong Joint Fund[U180120020] ; program for Liaoning Excellent Talents in University[LR2017009]
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/23582
Collection机器人学研究室
Corresponding AuthorGou, Yu
Affiliation1.College of Computer Science and Technology, Jilin University, Changchun 130012, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, Dalian 116024, China
Recommended Citation
GB/T 7714
Liu J,Zhang, Tong,Han, Guangjie,et al. TD-LSTM: Temporal dependence-based LSTM networks for marine temperature prediction[J]. Sensors (Switzerland),2018,18(11):1-13.
APA Liu J,Zhang, Tong,Han, Guangjie,&Gou, Yu.(2018).TD-LSTM: Temporal dependence-based LSTM networks for marine temperature prediction.Sensors (Switzerland),18(11),1-13.
MLA Liu J,et al."TD-LSTM: Temporal dependence-based LSTM networks for marine temperature prediction".Sensors (Switzerland) 18.11(2018):1-13.
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