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Retraction Note: Hybrid deep learning framework for cardiovascular disease diagnosis and prognosis using GAN, LSTM, GRU, VARMA, and deep DynaQ network. [PDF]

Sci Rep
A V, J A.
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Global temperature anomaly prediction by using additive twin LSTM networks. [PDF]

Sci Rep
Keles C, Baran B, Alagoz BB.
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Design of security situation awareness power grid SCADA system based on improved GWO-LSTM. [PDF]

Sci Rep
Chen Z, Zheng H, Gao L, Qiu F, Huang H, Liu S.   +5 more
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Multi-hour and multi-site air quality index forecasting in Beijing using CNN, LSTM, CNN-LSTM, and spatiotemporal clustering

Expert Systems With Applications, 2021
Effective air quality forecasting models are helpful for timely prevention and control of air pollution. However, the spatiotemporal distribution characteristics of air quality have not been fully considered in previous model development.
Jiaqiang Liao, Wei Sun
exaly   +2 more sources

Host–Parasite: Graph LSTM-in-LSTM for Group Activity Recognition

IEEE Transactions on Neural Networks and Learning Systems, 2021
This article aims to tackle the problem of group activity recognition in the multiple-person scene. To model the group activity with multiple persons, most long short-term memory (LSTM)-based methods first learn the person-level action representations by several LSTMs and then integrate all the person-level action representations into the following ...
Xiangbo Shu, Liyan Zhang, Yunlian Sun
exaly   +3 more sources

LSTM

2021
. LSTM- .
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