Name
Abstract | ||
|---|---|---|
Nowadays more and more people in the big city rely on public transportations while they go to work or school. MRT (Mass Rapid Transit) is one of the most modern transportations in Taipei. It is a great traffic tool to relieve the pressure of rush hours. According to the statistics, each day there will be over one million of passengers taking the MRT in Taipei. In this paper, we will be predicting MRT passenger flow with random forest, by using different factors collected from the Taipei Main station as input for training. The result shows that some of the influenced factors are important to affect the prediction of the passenger flow. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICAwST.2017.8256497 | 2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST) |
Keywords | Field | DocType |
MRT,passenger flow,random forest,prediction model | Decision tree,Mass rapid transit,Computer science,Transport engineering,Flow (psychology),Random forest | Conference |
ISSN | ISBN | Citations |
2325-5986 | 978-1-5386-2966-6 | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yi Chen Shiao | 1 | 0 | 0.34 |
| Lijuan Liu | 2 | 0 | 0.68 |
| Qiangfu Zhao | 3 | 214 | 62.36 |
| Rung-Ching Chen | 4 | 331 | 37.37 |