Abstract Accurate daily streamflow forecasting is crucial for effective flood control and water management. Decomposition ensemble models have proven to be effective in daily streamflow forecasting. However, it is important to recognize that the performance of streamflow forecasting within the decomposition e...
The coasts of the Northeastern United States experience wind and flood damage as a result of extratropical cyclones (such as Nor’easters). However, recorded data is limited for hazard analysis and resilience evaluation. This paper describes a method that can efficiently augment the time series of...
The trapezoids represents the shrinking nature of the encoder, and the expanding nature of the decoder. The classification layer is a fully connected layer with a softmax activation function. 3.2. First proposed approach: Latent layer classification on a variational autoencoder (LLC-VAE) The first...
It consists of an encoder and a decoder, in which the encoding process transfers the input features to the hidden space. The decoding process performs reconstruction learning on the input features. In the AE training process, the loss function is the deviation of the deterministic value between ...
trains using autoencoder‑based deep learning models Jeonguk Seo 1,Yunu Kim 2, Jisung Ha 1, Dongyoup Kwak 3, Minsam Ko 1 & Mintaek Yoo 4* We propose a method for detecting earthquakes for high-speed trains based on unsupervised anomaly-detection techniques...
Compared with the conventional CNN models, the HA-EDNet framework can deal with repeated calculation and observe objects from multi-scale and long-distance perspectives. The main contributions are summarized as follows: (1) An end-to-end encoder–decoder fully convolution network called EDNet is ...
Security research in this area has two key issues: the lack of datasets for training artificial intelligence (AI)-based intrusion detection models and the fact that most existing datasets concentrate only on one type of network traffic. Thus, this study introduces Dragon_Pi, an intrusion detection...
Security research in this area has two key issues: the lack of datasets for training artificial intelligence (AI)-based intrusion detection models and the fact that most existing datasets concentrate only on one type of network traffic. Thus, this study introduces Dragon_Pi, an intrusion detection...
In short, in this study, the effectiveness of PFs for water stream extraction was verified and the proposed FFEDN can further improve the accuracy of water stream extraction. Keywords: water stream extraction; encoder-decoder network; synthetic aperture radar (SAR); polarimetric feature (PF); ...
The contents in the bracket, such as (CNN, GRU), represent that the decoder of VAEGAN is CNN and that of LSM models is GRU, respectively. Table 6. Comparison of the transferability of different models (LX to GG). The loss during training is one of the evaluators reflecting the ...