Improving non-intrusive load disaggregation through an attention-based deep neural network

HIGHLIGHTS

  • who: Veronica Piccialli and Antonio M. Sudoso from the Department of Civil and Computer Engineering, University of Rome Tor Vergata, Rome, Italy have published the research: Improving Non-Intrusive Load Disaggregation through an Attention-Based Deep Neural Network, in the Journal: Energies 2021, 14, 847. of /2021/
  • what: The authors propose a network that combines a regression subnetwork with a classification subnetwork for solving the NILM problem. The authors propose a RNN-based encoder-decoder model to extract appliance specific power usage from the aggregated signal and the authors enhance it with a scalable and . . .

     

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