RNN-LSTM: From applications to modeling techniques and beyond ...
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, 2022). …
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 gating …
Long Short-Term Memory - an overview | ScienceDirect Topics
LSTM, or long short-term memory, is defined as a type of recurrent neural network (RNN) that utilizes a loop structure to process sequential data and retain long-term information through a memory cell, …
A survey on long short-term memory networks for time series prediction
Jan 1, 2021 · Recurrent neural networks and exceedingly Long short-term memory (LSTM) have been investigated intensively in recent years due to their ability to model and predict nonlinear time-variant …
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-ARIMA as a hybrid approach in algorithmic investment strategies
Jun 23, 2025 · This study makes a significant contribution to the growing field of hybrid financial forecasting models by integrating LSTM and ARIMA into a novel algorithmic investment strategy. …
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 detailed overview on …
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 theoretical advantages of …
A cellular automata model coupled with partitioning CNN-LSTM and …
Feb 1, 2024 · Urbanisation is a key aspect of land use change (LUC), and accurately modelling of urban LUC is crucial for sustainable development. Cellular automata…
NOA-LSTM: An efficient LSTM cell architecture for time series ...
Mar 15, 2024 · The LSTM architecture has been criticized for being ad-hoc and having many variable components whose contributions are not evident. Consequently, it is uncertain whether the popular …