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 …
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 · All major open source machine learning frameworks offer efficient, production-ready implementations of a number of RNN and LSTM network architectures. Naturally, some …
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 …
Load forecasting method based on CNN and extended LSTM
Dec 1, 2024 · In this paper, we proposed a hybrid model utilizing CNN and dilated LSTM. The CNN effectively extracts comprehensive features from the load data, while the extended LSTM …
Convolutional LSTM - an overview | ScienceDirect Topics
Convolutional LSTM (ConvLSTM) is an important extension of LSTM, which takes a series of two-dimensional matrices as the input. ConvLSTM has been used in the spatial–temporal …
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 …
Predicting stock market index using LSTM - ScienceDirect
Sep 15, 2022 · The rapid advancement in artificial intelligence and machine learning techniques, availability of large-scale data, and increased computational capabi…
Performance analysis of neural network architectures for time …
Dec 1, 2025 · LSTM-based hybrid architectures, particularly LSTM-RNN and LSTM-GRU configurations, demonstrate reliable performance across multiple domains and should be …