Tag Archives: AEMET

CNN-based architectures can be used to increase the prediction lead time of thunderstorms

Our latest research shows that Convolutional Neural Networks (CNN)-based architectures can be used to increase the prediction lead time of thunderstorms in the aviation field. These results are published in the journal paper titled “Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks”. A study written by Aniel Jardinesa, Hamidreza Eivazib, Elias Zeab, Javier García-Herasa,Continue reading “CNN-based architectures can be used to increase the prediction lead time of thunderstorms”