Traffic Prediction of Space-Integrated Ground Information Network Using the GTCN Algorithm
Round 1
Reviewer 1 Report
- Why only 30% data were used for prediction?
- Why isn't there any training time for ARIMA model?
- Include a flowchart for the proposed method.
- How about comparison of traffic flow prediction models for one test day? Why was this not considered?
- Can the method be represented in real-world scenario? If yes how, show a diagram of setup.
Author Response
Thank you for your comments, please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
This manuscript presents the traffic characteristics of the Space-Integrated Ground Information Intelligent Network for dealing with the traffic prediction problem. And, they propose the GTCN and the TCN algorithm. The manuscript is interesting and shows a new algorithm to use for future cases. Although the results are good in comparison with the state of the art. I suggest:
- Check equation 7, it looks there are missing symbols
- Reduce the size of figure 6
- page 13 check structure, there is a cut line
- you shouldn't give the results already at the introduction, you should comment them at the abstract
- You must explain all figure (step by step)
- You must describe how you calculated the metrics Maximum Instantaneous Memory Usage (MIMU) and Average 151
Memory Usage (AMU) - Merge the plots from figure 8, into a single one (overlapping lines) or create a multiplot
- How is it possible that you've proposed TCN when it is already in python library? Please, justify this.
Author Response
Thank you for your comments, please see the attachment.
Author Response File: Author Response.docx
Round 2
Reviewer 2 Report
The manuscript has improved considerably after addressing the commented changes.
