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 …
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 …
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 …
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…
Explicit speed-integrated LSTM network for non-stationary …
Feb 1, 2025 · To this end, this paper proposes novel explicit speed-integrated LSTM (SI-LSTM) models to enhance the representation accuracy of non-stationary vibration signals and …
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…
Improved network anomaly detection system using optimized …
May 10, 2025 · The PSO-optimized Autoencoder-LSTM model is designed to counter such threats by learning subtle, long-term patterns in network traffic, ensuring early detection and mitigating …
Improving streamflow prediction in the WRF-Hydro model with …
Feb 1, 2022 · In this approach, LSTM was employed to predict the residual errors of WRF-Hydro; in contrast, the conventional approach with LSTM predicts streamflow directly. Here, we …
A multihead LSTM technique for prognostic prediction of soil …
May 1, 2023 · Prognostic prediction of soil moisture is a critical step in various fields such as geotechnical engineering, agriculture, geology, hydrology, and cli…
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 …