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 · 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 …

Mar 1, 2020 · Because of their effectiveness in broad practical applications, LSTM networks have received a wealth of coverage in scientific journals, technical blo…

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 …

In this work, we bridge this gap by introducing pseudo-sequential representations to adapt LSTM networks for steady-state EHD flows. By reformulating spatial dependencies as learnable …

Dec 14, 2025 · This paper presents a novel hybrid deep learning architecture, VMD-Informer-LSTM, for accurate and scalable solar radiation forecasting. The proposed …

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 …

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 …

Aug 1, 2024 · We propose an interpretable flood forecasting hybrid model based on Transformer, LSTM, and Adaptive Random Search Algorithm (AGRS), termed as AGRS-LSTM …