RNN-LSTM: From applications to modeling techniques and beyond ...
Jun 1, 2024 · Long Short-Term Memory (LSTM) is a popular Recurrent Neural Network (RNN) algorithm known for its ability to effectively analyze and process sequential data with long-term dependencies. …
Long Short-Term Memory Network - an overview - ScienceDirect
Jul 7, 2020 · A Long Short-Term Memory Network, also known as LSTM, is an advanced recurrent neural network that uses "gates" to capture both long-term and short-term memory. These gates help …
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 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 …
LSTM and GRU type recurrent neural networks in model predictive …
Jun 1, 2025 · Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) neural networks are known for their capability of modeling numerous dynamical phenomena.…
Performance analysis of neural network architectures for time series ...
Dec 1, 2025 · RNNs, LSTM networks, and GRUs are particularly useful for time series analysis, as they are capable of handling sequential data and learning long-term dependencies. RNNs were …
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 practitioners, …
Singular Value Decomposition-based lightweight LSTM for time series ...
Jan 1, 2026 · Long–short-term memory (LSTM) neural networks are known for their exceptional performance in various domains, particularly in handling time series dat…
Prediction of shield tunneling-induced ground settlement using LSTM ...
Jul 1, 2025 · Numerous advanced deep learning models have been applied to forecast shield tunneling-induced ground settlement to mitigate the adverse impacts of exc…
Hybrid machine learning model combining of CNN-LSTM-RF for time …
Sep 1, 2024 · The CNN-LSTM-RF hybrid model combines the strengths of convolutional neural networks (CNNs) for spatial feature extraction, Long Short-Term Memory (LSTM) networks for …