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TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction
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 depth...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263690/ https://www.ncbi.nlm.nih.gov/pubmed/30404217 http://dx.doi.org/10.3390/s18113797 |
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author | Liu, Jun Zhang, Tong Han, Guangjie Gou, Yu |
author_facet | Liu, Jun Zhang, Tong Han, Guangjie Gou, Yu |
author_sort | Liu, Jun |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6263690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-62636902018-12-12 TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction Liu, Jun Zhang, Tong Han, Guangjie Gou, Yu Sensors (Basel) Article 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. MDPI 2018-11-06 /pmc/articles/PMC6263690/ /pubmed/30404217 http://dx.doi.org/10.3390/s18113797 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Jun Zhang, Tong Han, Guangjie Gou, Yu TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction |
title | TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction |
title_full | TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction |
title_fullStr | TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction |
title_full_unstemmed | TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction |
title_short | TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction |
title_sort | td-lstm: temporal dependence-based lstm networks for marine temperature prediction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263690/ https://www.ncbi.nlm.nih.gov/pubmed/30404217 http://dx.doi.org/10.3390/s18113797 |
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