RNN-LSTM: From applications to modeling techniques and …
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 sequential data with long-term …
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 …
Long Short-Term Memory - an overview | ScienceDirect Topics
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 …
A survey on long short-term memory networks for time series …
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 …
Fundamentals of Recurrent Neural Network (RNN) and Long Short …
2020年3月1日 · All major open source machine learning frameworks offer efficient, production-ready implementations of a number of RNN and LSTM network architectures. Naturally, some …
Load forecasting method based on CNN and extended LSTM
2024年12月1日 · In this paper, we proposed a hybrid model utilizing CNN and dilated LSTM. The CNN effectively extracts comprehensive features from the load data, while the extended LSTM …
Working Memory Connections for LSTM - ScienceDirect
2021年12月1日 · In our experiments, we show that an LSTM equipped with Working Memory Connections achieves better results than comparable architectures, thus reflecting the …
Predicting stock market index using LSTM - ScienceDirect
2022年9月15日 · The rapid advancement in artificial intelligence and machine learning techniques, availability of large-scale data, and increased computational capabi…
A survey on anomaly detection for technical systems using LSTM …
2021年10月1日 · 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 …
Improved network anomaly detection system using optimized …
2025年5月10日 · 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 …