RNN-LSTM: From applications to modeling techniques and …
Jun 1, 2024 · LSTM has been specifically designed to address the issue of vanishing gradients, which makes vanilla RNNs unsuitable for learning long-term dependencies (Jaydip and Sidra, …
Long Short-Term Memory Network - an overview - ScienceDirect
Network LSTM refers to a type of Long Short-Term Memory (LSTM) network architecture that is particularly effective for learning from sequences of data, utilizing specialized structures and …
Fundamentals of Recurrent Neural Network (RNN) and Long Short …
Mar 1, 2020 · Because of their effectiveness in broad practical applications, LSTM networks have received a wealth of coverage in scientific journals, technical blo…
Lstm - an overview | ScienceDirect Topics
Aug 31, 2018 · LSTM, or Long Short-Term Memory networks, is defined as a type of neural network that extends Recurrent Neural Networks (RNN) to handle long-term dependencies by …
Performance analysis of neural network architectures for time …
Dec 1, 2025 · LSTM-based hybrid architectures, particularly LSTM-RNN and LSTM-GRU configurations, demonstrate reliable performance across multiple domains and should be …
A survey on anomaly detection for technical systems using LSTM …
Oct 1, 2021 · However, due to the recent emergence of different LSTM approaches that are widely used for different anomaly detection purposes, the present paper aims to present a …
Working Memory Connections for LSTM - ScienceDirect
Dec 1, 2021 · In our experiments, we show that an LSTM equipped with Working Memory Connections achieves better results than comparable architectures, thus reflecting the …
EA-LSTM: Evolutionary attention-based LSTM for time series …
Oct 1, 2019 · This paper proposes an evolutionary attention-based LSTM model (EA-LSTM), which is trained with competitive random search for time series prediction. During temporal …
Fundamentals of Recurrent Neural Network (RNN) and Long Short …
Mar 1, 2020 · All major open source machine learning frameworks offer efficient, production-ready implementations of a number of RNN and LSTM network architectures. Naturally, some …
A CNN-LSTM based deep learning model with high accuracy and …
Feb 14, 2024 · CNN-LSTM model was used to predict the Beijing air quality index and compared with other traditional basic models, and the CNN-LSTM model showed better prediction ability …