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
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 …
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 · All major open source machine learning frameworks offer efficient, production-ready implementations of a number of RNN and LSTM network architectures. Naturally, some practitioners, …
Performance analysis of neural network architectures for time series ...
Dec 1, 2025 · LSTM-based hybrid architectures, particularly LSTM-RNN and LSTM-GRU configurations, demonstrate reliable performance across multiple domains and should be considered as primary …
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 …
PI-LSTM: Physics-informed long short-term memory ... - ScienceDirect
Oct 1, 2023 · The PI-LSTM network, inspired by and compared with existing physics-informed deep learning models (PhyCNN and PhyLSTM), was validated using the numerical simulation results of …
Coupling LSTM neural networks and state-space models through ...
Jan 1, 2025 · Long short-term memory (LSTM) neural networks and state-space models (SSMs) are effective tools for time series forecasting. Coupling these methods to…
EA-LSTM: Evolutionary attention-based LSTM for time series prediction
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 relationship …