TD-LSTM: Temporal dependence-based LSTM networks for marine temperature prediction | |
Liu J(刘军)1,3; Zhang, Tong3; Han, Guangjie2; Gou, Yu3 | |
刊名 | SENSORS |
2018 | |
卷号 | 18期号:11页码:1-13 |
关键词 | Long Short-term Memory (Lstm) Temporal Dependence Sea Surface Temperature (Sst) Prediction |
ISSN号 | 1424-8220 |
产权排序 | 1 |
英文摘要 | 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. |
资助项目 | National 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] |
WOS关键词 | FORECASTS ; SST |
WOS研究方向 | Chemistry ; Electrochemistry ; Instruments & Instrumentation |
语种 | 英语 |
WOS记录号 | WOS:000451598900207 |
资助机构 | National 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 |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/23582] |
专题 | 沈阳自动化研究所_机器人学研究室 |
通讯作者 | Gou, Yu |
作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, Dalian 116024, China 3.College of Computer Science and Technology, Jilin University, Changchun 130012, China |
推荐引用方式 GB/T 7714 | Liu J,Zhang, Tong,Han, Guangjie,et al. TD-LSTM: Temporal dependence-based LSTM networks for marine temperature prediction[J]. SENSORS,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,18(11),1-13. |
MLA | Liu J,et al."TD-LSTM: Temporal dependence-based LSTM networks for marine temperature prediction".SENSORS 18.11(2018):1-13. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论