Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 13, issue 12
Articles | Volume 13, issue 12
https://doi.org/10.5194/gmd-13-6237-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-6237-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 12
Model evaluation paper
 | 
09 Dec 2020
Model evaluation paper |  | 09 Dec 2020

Using wavelet transform and dynamic time warping to identify the limitations of the CNN model as an air quality forecasting system

Ebrahim Eslami, Yunsoo Choi, Yannic Lops, Alqamah Sayeed, and Ahmed Khan Salman

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Short summary
As using deep learning algorithms has become a popular data analytic technique, atmospheric scientists should have a balanced perception of their strengths and limitations so that they can provide a powerful analysis of complex data with well-established procedures. This study addresses significant limitations of an advanced deep learning algorithm, the convolutional neural network.
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