Results 41 to 50 of about 143,911 (316)
LSTM-GWO performance evaluation with experiment 6.
, 2022 LSTM-GWO performance evaluation with experiment 6.
Naglaa Fathy Hassan (13189914) +2 more
core +1 more source
CoRR, 2018 We propose Nested LSTMs (NLSTM), a novel RNN architecture with multiple levels of memory. Nested LSTMs add depth to LSTMs via nesting as opposed to stacking. The value of a memory cell in an NLSTM is computed by an LSTM cell, which has its own inner memory cell.
Joel Ruben Antony Moniz +1 more
openaire +3 more sources
High insecticide resistance in the major malaria vector Anopheles coluzzii in Chad Republic
Infectious Diseases of Poverty, 2019 Background The Sahel region of Chad Republic is a prime candidate for malaria pre-elimination. To facilitate pre-elimination efforts in this region, two populations of Anopheles coluzzii from Central Chad Republic were characterized, their insecticide ...
Sulaiman S. Ibrahim +8 more
doaj +1 more source
LSTM-Attention network structure.
, 2020 LSTM-Attention network structure.
Changjun Zhou (451444) +2 more
core +1 more source
Indylstms: Independently Recurrent LSTMS [PDF]
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 8 pages, submitted to ICDAR ...
Pedro Gonnet, Thomas Deselaers
openaire +3 more sources
Foods, 2023 Due to its “generally recognized as safe status” (GRAS) and moderate treatment temperatures, non-thermal plasma (NTP) has lately been considered a suitable replacement for chemicals in the modification of food properties and for preserving food quality ...
Muhammad Jehanzaib Khan +5 more
doaj +1 more source
LSTM-GWO performance evaluation with experiment 2.
, 2022 LSTM-GWO performance evaluation with experiment 2.
Naglaa Fathy Hassan (13189914) +2 more
core +1 more source
2017 International Joint Conference on Neural Networks (IJCNN), 2017 Previous RNN architectures have largely been superseded by LSTM, or "Long Short-Term Memory". Since its introduction, there have been many variations on this simple design. However, it is still widely used and we are not aware of a gated-RNN architecture that outperforms LSTM in a broad sense while still being as simple and efficient.
Andrew Pulver, Siwei Lyu
openaire +4 more sources
Time Series Prediction Based on LSTM-Attention-LSTM Model
IEEE Access, 2023 Time series forecasting uses data from the past periods of time to predict future information, which is of great significance in many applications. Existing time series forecasting methods still have problems such as low accuracy when dealing with some non-stationary multivariate time series data forecasting.
Xianyun Wen, Weibang Li
openaire +3 more sources
LSTM-GWO prediction and actual scores with experiment 4.
, 2022 LSTM-GWO prediction and actual scores with experiment 4.
Naglaa Fathy Hassan (13189914) +2 more
core +1 more source