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TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction
Jun Liu1,2, Tong Zhang3, Guangjie Han4
1College of Computer Science and Technology, Jilin University, Changchun 130012, China. liujun1509@jlu.edu.cn.
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.
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