I have a time series dataset containing hourly data from a few year, like below. Let's assume that I want to make prediction for the next 3 hours (2021-01-01 19:00, 2021-01-01 20:00, 2021-01-01 21:00). The output from model (e.g. LSTM) is the following sequence: [Feature_1(t+1), Feature_1(t+2), Feature_1(t+3)]. One of the features of my training data is weather data.
Can I use data, that I already know in my model? I would like to use the weather forecast for the next hours to improve my predctions.
For example at
2021-01-01 18:00 i know value
Weather_feature in time
t(0) but also i know already
(t+3). How can i use it in the model?
At the moment, this is what one training sample looks like:
[[Feature_1(t-n), Weather_feature(t-n)]...[Feature_1(t-1),Weather_feature(t-1), [Feature_1(t0), Weather_feature(t0)]]