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 …
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 sequentia…
PI-LSTM: Physics-informed long short-term memory
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 …
Interpretable spatio-temporal attention LSTM model for flood ...
Aug 25, 2020 · LSTM-based methods Long Short Term Memory (LSTM) is a modified version of recurrent neural networks, which is proposed to solve the problem of long-distance (time) …
Stock Market Prediction Using LSTM Recurrent Neural Network
Jan 1, 2020 · It has never been easy to invest in a set of assets, the abnormally of financial market does not allow simple models to predict future asset values wi…
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…
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…
Hybrid machine learning model combining of CNN-LSTM-RF for …
Sep 1, 2024 · The CNN-LSTM-RF hybrid model combines the strengths of convolutional neural networks (CNNs) for spatial feature extraction, Long Short-Term Memory (LSTM) networks for …
Improving urban flood prediction using LSTM-DeepLabv3+ and …
Feb 1, 2024 · LSTM-DeepLabv3+ achieves the highest prediction accuracy. Deep learning models have become increasingly popular for flood prediction due to their superior accuracy …
Physics-informed multi-LSTM networks for metamodeling of …
Sep 1, 2020 · This paper introduces an innovative physics-informed deep learning framework for metamodeling of nonlinear structural systems with scarce data. The ba…