Hi @ricardoV94 ,

I am investigate some speed prediction for vehicle.

For example at time t=2, I can predict the velocity for t=3.

What if I want to train a model that at time t=2, I can predict velocity for time t=3, t=4, … for multiple steps.

I wonder how can I train this model.

I have an idea of manipulating with the observed data, which means,

In original, I train a data which can observe t=2 and t=3 only.

But now I train with observed data including t=2, t=3, t=4 and so on.

But the concept still value at t3 depends on t2 and so on.

I working on time series data, so I working with sequence of data or I prefer to call it a buffer or window.

For example, I have a window size of 60, which are the past and current state at time 60, then I will predict value at t=61.

So at t=60, I can predict value at t=61.

Now I wish to predict t=61, 62 and so on, with current state of t=60.

Please let me know if my elaboration still not clear enough.

Thanks