Prediction of Sea Surface Temperature Using Long Short-Term Memory
TLDR
This letter adopts long short-term memory (LSTM) to predict sea surface temperature (SST), and makes short- and long-term prediction, including weekly mean and monthly mean, and the model’s online updated characteristics are presented.Abstract:
This letter adopts long short-term memory (LSTM) to predict sea surface temperature (SST), and makes short-term prediction, including one day and three days, and long-term prediction, including weekly mean and monthly mean The SST prediction problem is formulated as a time series regression problem The proposed network architecture is composed of two kinds of layers: an LSTM layer and a full-connected dense layer The LSTM layer is utilized to model the time series relationship The full-connected layer is utilized to map the output of the LSTM layer to a final prediction The optimal setting of this architecture is explored by experiments and the accuracy of coastal seas of China is reported to confirm the effectiveness of the proposed method The prediction accuracy is also tested on the SST anomaly data In addition, the model’s online updated characteristics are presentedread more
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References
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Journal ArticleDOI
Long short-term memory
TL;DR: A novel, efficient, gradient based method called long short-term memory (LSTM) is introduced, which can learn to bridge minimal time lags in excess of 1000 discrete-time steps by enforcing constant error flow through constant error carousels within special units.
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TL;DR: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language.
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Deep learning
TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
Posted Content
Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Andreas Müller,Joel Nothman,Gilles Louppe,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +18 more
TL;DR: Scikit-learn as mentioned in this paper is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.