… To achieve better accuracy, we proposed a hybrid model called LSTM-GRU of deep learning
that fused the GRU (gated recurrent unit) and LSTM (long short-term memory). The results …

… the GRU has less complexity in the architecture when compared to LSTM, thus, making it
light-weight. We have performed the anomaly detection experiments using GRU and LSTM and …

… architectures), we found that the vanilla LSTM and GRU models … LSTM unit and (2) a
GRU. We used the two hybrid models (the joint CNN-and-LSTM model and the joint CNN-and-GRU …

… CNN, LSTM, and GRU are displayed in Figure 3. The precision of the LSTM is higher than
that of the CNN and GRU, … The F1 score, review, and precision for CNN, LSTM, and GRU are …

… being easy-to-analyze make GRU stand out compared to LSTM [36]. GRU has a similar
structure when compared to LSTM units. Unlike LSTM, GRU has a reset and update gateway …

… We employ different deep neural network algorithms including GRU, LSTM, and CNN to
study the effectiveness of adversarial attacks against these models on the CSE-CIC-IDS2018 …

… faced by the perception layer of the Internet of Things, this article adopts an intelligent
and lightweight GRU-LSTM algorithm intrusion detection technology. Machine learning is an …

… Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural network to Internet of Things
(IoT… The experimental results show that the GRU-based model improves the performance by …

… Attack detection: The LSTM method and GRU method are combined (LSTM-GRU) for detecting
the instruction attacks in IoT within a specific time from unauthorized access. This method …

… -layer model uses GRU. Compared to LSTM, the construction of GRU is simpler because it
reduces one gate and matrix multiplication is less strained. Therefore, the GRU can save a lot …