The intuition here is to PASS the time-series window, which predicts the forecasted output for Simple LSTM and Reconstructs the input sequence for LSTM Autoencoder by using Encoder-Decoder network ...

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This paper proposes an Autoencoder Long Short-Term Memory (AE-LSTM) algorithm to improve anomaly detection. We evaluate and compare the efficacy of AE-LSTM against the benchmark Deep Neural Network ...

Abstract: By pushing computing resources from the cloud to the network edge close to mobile ... Inspired by concept drift, this paper proposes B-Detection, a boosting Long Short-Term Memory (LSTM) ...

To address the issue, this study proposed an innovative anomaly detection algorithm, namely the LSTM Autoencoder with Gaussian Mixture Model (LAGMM). This model supports anomalous CAV trajectory ...