RNN-LSTM: From applications to modeling techniques and …
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 …
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 …
A survey on long short-term memory networks for time series …
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 …
LSTM-ARIMA as a hybrid approach in algorithmic investment …
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 …
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 …
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…
Enhancing streamflow forecasting using an LSTM hybrid model …
Consequently, LSTM attracts considerable attention and has been rigorously validated in hydrological forecasting. Chen et al. (2020) compared an artificial neural network (ANN) with …
PI-LSTM: Physics-informed long short-term memory
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 …
Singular Value Decomposition-based lightweight LSTM for time …
Long–short-term memory (LSTM) neural networks are known for their exceptional performance in various domains, particularly in handling time series dat…
Model Predictive Control when utilizing LSTM as dynamic models
Aug 1, 2023 · The prediction model is the most important part of an MPC strategy. The accuracy of such a model influences the quality of predictions and control per…