Research Article
Mass Rapid Transit System Passenger Traffic Forecast Using a Re-Sample Recurrent Neural Network
Table 5
The output and input variable list.
| | Column name | Output variable |
| | V1 | Severe |
| | V2 | Moderate |
| | V3 | Light |
| | V4 | Normal |
| | Column name | Input variable |
| | c_sch | scheduled capacity |
| | c_unsch | unscheduled capacity |
| | p_vol | average passenger loads for the segment for day d that is within the previous 28 days. |
| | rain | Raining day variable for day d, if rains, r=1 otherwise 0. |
| | Coliseum | Event variable (0 / 1) |
| | Fremont | Event variable (0 / 1) |
| | Giants | Event variable (0 / 1) |
| | Berkeley | Event variable (0 / 1) |
| | Hardly | Event variable (0 / 1) |
| | Autoshow | Event variable (0 / 1) |
| | Dreamforce | Event variable (0 / 1) |
| | ArtMurmur | Event variable (0 / 1) |
| | holidy | h=1 if day d is a holiday, otherwise, h = 0 |
| | V14 | schedule_type:WE |
| | V15 | schedule_type:SA |
| | V16 | schedule_type:SU |
| | V17 | Month:January |
| | V18 | Month:February |
| | V19 | Month:March |
| | V20 | Month:April |
| | V21 | Month: May |
| | V22 | Month:June |
| | V23 | Month:July |
| | V24 | Month:August |
| | V25 | Month:September |
| | V26 | Month:October |
| | V27 | Month:November |
| | V28 | Month:December |
| | V29 | day of week:Sunday |
| | V30 | day of week:Monday |
| | V31 | day of week:Tuesday |
| | V32 | day of week:Wednesday |
| | V33 | day of week:Thursday |
| | V34 | day of week:Friday |
| | V35 | day of week:Saturday |
| | V36 | month of week | 1 | | V37 | month of week | 2 | | V38 | month of week | 3 | | V39 | month of week | 4 |
| | V40 | Time period dummy variable | 5am to 8am | | V41 | 8am to 11am | | V42 | 11am to 2pm | | V43 | 2pm to 5pm | | V44 | 5pm to 8pm | | V45 | 8pm to 11pm |
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