2025年5月1日 · The soil characteristic data is represented by root zone soil moisture, which is derived from raster data. The LSTM-FKAN coupled with feature extraction technique …

2020年7月7日 · A Long Short-Term Memory Network, also known as LSTM, is an advanced recurrent neural network that uses "gates" to capture both long-term and short-term memory. …

2023年10月1日 · The PI-LSTM network, inspired by and compared with existing physics-informed deep learning models (PhyCNN and PhyLSTM), was validated using the numerical simulation …

LSTM-based hybrid architectures, particularly LSTM-RNN and LSTM-GRU configurations, demonstrate reliable performance across multiple domains and should be considered as …

2024年6月1日 · Long Short-Term Memory (LSTM) is a popular Recurrent Neural Network (RNN) algorithm known for its ability to effectively analyze and process sequentia…

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 …

2023年7月1日 · LSTM has been previously developed and is utilized to serve as a reference model, while WaveNet and 2D CNN (i.e., it deals with the data in coupled time–frequency …

2021年1月1日 · 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 …

This model combines the advantages of both Transformer and LSTM architectures, utilizing the Transformer's self-attention mechanism to capture long-term dependencies while modeling …

2025年6月23日 · 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 …