I'm not sure what this type of data is called, so I will give an example of the type of data I am working with:
- A city records its inflow and outflow of different types of vehicles every hour. More specifically, it records the engine size. The output would be the pollution level X hours after the recorded hourly interval.
It's worth noting that the data consists of individual vehicle engine size, so they cant be aggregated. This means the 2 input vectors (inflow and outflow) will be of variable length (different number of vehicles would be entering and lraving every hour) and I'm not sure how to handle this. I could aggregate and simply sum the number of vehicles, but I want to preserve any patterns in the data. E.g. perhaps there is a quick succession of several heavy motorbike engines, denoting a biker gang have just entered the city and are known to ride recklessly, contributing more to pollution than the sum of its parts.
Any insight is appreciated.