An adaptive scale sea surface temperature predicting method based on deep learning with attention mechanism
J Xie, J Zhang, J Yu, L Xu - IEEE Geoscience and Remote …, 2019 - ieeexplore.ieee.org
Sea surface temperature (SST) prediction plays an important role in ocean-related fields. It is
challenging due to the nonlinear temporal dynamics with changing complex factors and the …
challenging due to the nonlinear temporal dynamics with changing complex factors and the …
Sea surface temperature prediction with memory graph convolutional networks
We develop a memory graph convolutional network (MGCN) framework for sea surface
temperature (SST) prediction. The MGCN consists of two memory layers: one graph layer …
temperature (SST) prediction. The MGCN consists of two memory layers: one graph layer …
Spatiotemporal Meteorological Prediction Based on Fully Convolutional Neural Network
J Zhang, B Wang, M Hua, Z Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Accurate prediction of meteorological data is critical for enhancing the capacity to respond to
climate change, reducing disaster risks, and ensuring the sustainable development of …
climate change, reducing disaster risks, and ensuring the sustainable development of …
Data-driven optimization of coastal sea level monitoring: Leveraging known patterns for enhanced reconstruction
E Kartal, A Altunkaynak, A Çelik - Regional Studies in Marine Science, 2024 - Elsevier
Efficiently configuring sea level monitoring stations is crucial for obtaining accurate
spatiotemporal data while managing operational and maintenance costs and addressing the …
spatiotemporal data while managing operational and maintenance costs and addressing the …
Hindcast and forecast of daily inundation extents using satellite SAR and altimetry data with rotated empirical orthogonal function analysis: Case study in Tonle Sap …
Abstract The Tonle Sap Lake (TSL) is the largest natural freshwater lake in Southeast Asia
and is called the “heart of the lower Mekong” due to its high aquatic biodiversity and is …
and is called the “heart of the lower Mekong” due to its high aquatic biodiversity and is …
Multilayer fusion recurrent neural network for sea surface height anomaly field prediction
Sea surface height anomaly (SSHA) is vitally important for climate and marine ecosystems.
This article develops a multilayer fusion recurrent neural network (MLFrnn) to achieve an …
This article develops a multilayer fusion recurrent neural network (MLFrnn) to achieve an …
Gssa: A network for short to medium-term regional sea surface temperature prediction
L Xiao, S Li, B Chen - IEEE Geoscience and Remote Sensing …, 2024 - ieeexplore.ieee.org
Accurate prediction of sea surface temperature (SST) is critical in marine sciences and
related disciplines. The task is rendered challenging by complex environmental factors and …
related disciplines. The task is rendered challenging by complex environmental factors and …
Global spatiotemporal graph attention network for sea surface temperature prediction
Z Gao, Z Li, J Yu, L Xu - IEEE Geoscience and Remote Sensing …, 2023 - ieeexplore.ieee.org
Accurately predicting sea surface temperature (SST) plays an important role in the study of
marine ecosystems and global climate. The SST prediction problem is usually formulated as …
marine ecosystems and global climate. The SST prediction problem is usually formulated as …
The Identification and Prediction of Mesoscale Eddy Variation via Memory in Memory With Scheduled Sampling for Sea Level Anomaly
R Nian, Y Cai, Z Zhang, H He, J Wu, Q Yuan… - Frontiers in Marine …, 2021 - frontiersin.org
Ocean mesoscale eddies are ubiquitous in world ocean and account for 90% oceanic
kinetic energy, which dominate the upper ocean flow field. Accurately predicting the …
kinetic energy, which dominate the upper ocean flow field. Accurately predicting the …
Hybrid model combining empirical mode decomposition, singular spectrum analysis, and least squares for satellite-derived sea-level anomaly prediction
Y Fu, X Zhou, W Sun, Q Tang - International journal of remote …, 2019 - Taylor & Francis
In this study, to meet the need for the accurate prediction of sea level anomaly (SLA), a
hybrid model is proposed. In this model, empirical mode decomposition is combined with …
hybrid model is proposed. In this model, empirical mode decomposition is combined with …