Capture and prediction of rainfall-induced landslide warning signals using an attention-based temporal convolutional neural network and entropy weight methods

HIGHLIGHTS

• who: Di Zhang and colleagues from the China Jiliang University, Hangzhou, China have published the research: Capture and Prediction of Rainfall-Induced Landslide Warning Signals Using an Attention-Based Temporal Convolutional Neural Network and Entropy Weight Methods, in the Journal: Sensors 2022, 22, 6240. of /2022/
• what: The authors propose an attention-based temporal convolutional neural_network for landslide warning signals prediction based on massive sensor data. The model is validated on two datasets obtained from rainfall-induced simulation experiments, and the model has high accuracy compared with similar landslide warning capture and prediction methods. The . . .
  

   

  

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