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Predicting plume concentrations in the urban area using a deep learning model

Asahi, Yuichi   ; Onodera, Naoyuki   ; Hasegawa, Yuta   ; Idomura, Yasuhiro   

We have developed a convolutional neural network (CNN) model to predict the plume concentrations in the urbanarea under uniform flow condition. By combining the Transformer or Multilayer Perceptron (MLP) layers with CNN model, our model can predict the plume concentrations from the building shapes, release points of plumeand time series data at observation stations.

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