Low-thrust trajectories: For Deep Learning Model Construction
Published in Journals, 2021
This database stores randomly generated low-thrust(LT) trajectories between NEAs. This database can be used for training interesting machine learning models. For example, using both feasible LT samples and infeasible samples to build a DNN classification model to distinguish LT transfer feasibilities. This database is valuable – obtaining such database requires hundreds of thousands of cores hours of high-performance computing system.
Database Summary
| Item | Description |
|---|---|
| Number of feasible trajectories | 300,000 |
| Number of feasible trajectories | 2,000,000 |
| File Format | .MAT |
| File Size | 3 GB |
| Precision | double-precision floating-point |
| Columns | exitflag, SPK1, SPK2, depart date, tof, spacecraft mass, PV1, PV2, Control Vectors |
Statistical
| Time of flight (days) | Initial Mass (KG) | Lambert Delta-V (KM/S) | |
|---|---|---|---|
| Min | 126 | 1053 | 0.15 |
| Max | 1460 | 3000 | 116.27 |
| Mean | 875.9 | 1830.5 | 45.00 |
| Median | 883 | 1732 | 41.65 |
Download Link
The link will be released later. Contact: ruida.space@gmail.com