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A data ensemble approach for real-time air quality forecasting using extremely randomized trees and deep neural networks.

Ebrahim EslamiAhmed Khan SalmanYunsoo ChoiAlqamah SayeedYannic Lops
Published in: Neural Comput. Appl. (2020)
Keyphrases
  • neural network
  • air quality
  • data sets
  • data analysis
  • active learning
  • data points
  • image data
  • spatial data
  • data quality
  • training data
  • pattern recognition
  • metaheuristic
  • random forests
  • streaming data
  • air pollution