Landslide risk prediction model using an attention-based temporal convolutional network connected to a recurrent neural network

HIGHLIGHTS

• who: . and collaborators from the National and Local Joint Engineering Laboratory of Disaster Monitoring Technology and Instruments, China Jiliang University, Hangzhou , have published the research work: Landslide Risk Prediction Model Using an Attention-based Temporal Convolutional Network Connected to a Recurrent Neural Network, in the Journal: (JOURNAL)
• what: In 2015, the aim of the BPNN was to predict slope deformation using daily and antecedent rainfall as input variables, and the model had great performance in accuracy . The contributions of this paper are shown as follows: First, the authors use the TOPSIS-Entropy method to access . . .
  

   

  

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