Can features passed into Conv1d layers be randomized?
Typically in a Conv1D layer for a time series, the features can be different measurements taken or recorded at the same time period. So they can be related to each other. For example, if you are trying to predict time=4 below, the question is whether there is a relationship between your features, meas1 and meas2? If so, you want to keep the features together to give you a better result.
| time | meas1 | meas2 |  
|------|-------|-------|  
| 1    | 4     | 6     |  
| 2    | 3     | 7     |  
| 3    | 2     | 8     |  
| 4    | ?     | ?     |  

You can look at cross-correlation in your dataset to answer this. Since this is time series data, you can use Pearson's correlation for this.