Published on Monday, 02 October 2023 08:51

As part of a thesis co-supervision agreement with Cairo University, Moetasm ElTaweel spent a third year at LISA, where he was supervised by S. Alfaro, A. Coman and G. Siour. Siour. The aim was to evaluate the ability of different artificial intelligence algorithms (Random Forest, XGboost) to predict the characteristics (speed and direction) of surface wind in the Cairo region. When the choice of predictive quantities is guided by physics (in particular, the selection of the horizontal gradient of atmospheric pressure is a considerable asset), the results obtained with the XGboost method are excellent (see Figures 1a and 1b, taken from ElTaweel et al., 2023).

 

 

 

 

 

More informations :

ElTaweel et al., 2023 : https://link.springer.com/article/10.1007/s00703-023-00999-6