Hello everybody, I’m about to write a kind of weather forecasting neural network and do not really find something good about transformers… My initial thought was a classic LSTM but in the last days I heard a lot of good stuff about Transformers, especially with multiple Input variables. Does Anybody here know more about that topic and would love to explain to me why I would use LSTM, Transformers or something else?
The data input will be a list of variables like temperature, humidity, elevation, wind speed, wind direction, …
The data output should be a 0-100 possibility of a specific event to occur.
I have some Billion labeled Data Points of from historical data.
Thx for your Help!