Research Article
Forecasting Beijing Transportation Hub Areas’s Pedestrian Flow Using Modular Neural Network
Table 1
Correlation analysis between pedestrian flow and influential factors.
| | Pearson correlation coefficient | Sig. (2-tailed) | |
| Regional land usage | 0.872 | 0.000 | 2200 | Effective width of sidewalks | −0.296 | 0.000 | 2200 | Proportion of reverse pedestrians | −0.146 | 0.000 | 2200 | Type of buffer | −0.242 | 0.000 | 1257 | On-street parking | 0.223 | 0.000 | 2200 | Isolation between nonmotor vehicles and motor vehicles | −0.072 | 0.002 | 1893 | Greening | −0.134 | 0.000 | 2199 | Inside motor vehicle flow | −0.168 | 0.000 | 2200 | Building facilities | −0.072 | 0.001 | 2200 | Distance between pedestrian and nonmotor vehicles | 0.166 | 0.000 | 1893 | Distance between pedestrian and motor vehicles | 0.131 | 0.000 | 2200 |
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