A comparative study of deep learning models on tropospheric ozone forecasting using feature engineering approach

HIGHLIGHTS

• who: Reza Rezaei and collaborators from the Department of Environmental Engineering, Hacettepe University, Ankara, Turkey have published the Article: A Comparative Study of Deep Learning Models on Tropospheric Ozone Forecasting Using Feature Engineering Approach, in the Journal: Atmosphere 2023, 14, 239. of 17/01/2023
• what: The authors demonstrate that addressing the evolution phases when developing the model architecture improves the performance of deep neural network models. After the calculation of each indicator`s weight, five models were developed to evaluate the health risk of the population, transportation damage risk, crop damage risk, economic loss . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.