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 …

Jun 1, 2024 · It aims to address how weight initialization and optimization techniques can bolster RNN-LSTM performance. This SLR offers a detailed overview across various applications and …

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 …

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 …

The proposed 3D temporal-spatial convolutional LSTM network offers a significant advantage by transforming 2D time series signals into 3D topomap-based scenes, effectively leveraging the …

Long Short-Term Memory (LSTM) networks [55] are a form of recurrent neural network that overcomes some of the drawbacks of typical recurrent neural networks. Any LSTM unit's cell …

Dec 1, 2025 · LSTM-based hybrid architectures, particularly LSTM-RNN and LSTM-GRU configurations, demonstrate reliable performance across multiple domains and should be …

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 …

Sep 1, 2024 · This study focuses on the hybrid model (CNN-LSTM-RF) to forecast SPG. The CNN-LSTM-RF hybrid model combines the strengths of convolutional neural networks (CNNs) …

Aug 31, 2018 · LSTM, or Long Short-Term Memory networks, is defined as a type of neural network that extends Recurrent Neural Networks (RNN) to handle long-term dependencies by …