Learning representations using rnn encoder-decoder for edge security control

HIGHLIGHTS

• who: Wei Guo and collaborators from the Information Center, Yunnan Power Grid Co, Ltd, Kunming, China have published the Article: Learning Representations Using RNN Encoder-Decoder for Edge Security Control, in the Journal: Computational Intelligence and Neuroscience of 23/05/2022
• what: The aim of this model is to learn the objective function f: RT u27f6 RT, where T represents the maximum length in the network access sequence.
• how: This paper introduced an unsupervised deep learning algorithm based on seq2seq which combined with the recurrent neural network and the autoencoder structure to realize . . .
  

   

  

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