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. …
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. …
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, …
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 …
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 …
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 …
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, …
An attention-aware LSTM model for soil moisture and soil temperature ...
Mar 1, 2022 · From this, we propose an attention-aware LSTM Model (ILSTM_Soil) by taking multi-feature attention, predictor attention and temporal attention into account. We first used LSTM to …
A critical review of RNN and LSTM variants in ... - ScienceDirect
Dec 1, 2024 · The selection and implementation of RNNs and LSTM variants, independently or in combination with other models, necessitates a profound grasp of their architectural intricacies and …