Research Article
Parking Volume Forecast of Railway Station Garages Based on Passenger Behaviour Analysis Using the LSTM Network
Table 1
Cosine similarity between each parking duration category.
| ā | C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 |
| C1 | 1 | 0.9667 | 0.8873 | 0.8250 | 0.5925 | 0.3873 | 0.2770 | 0.5713 | C2 | 0.9667 | 1 | 0.9341 | 0.8537 | 0.5783 | 0.3479 | 0.3479 | 0.5392 | C3 | 0.8873 | 0.9341 | 1 | 0.9399 | 0.6872 | 0.4494 | 0.3014 | 0.6358 | C4 | 0.8250 | 0.8537 | 0.9399 | 1 | 0.7533 | 0.5315 | 0.3538 | 0.7005 | C5 | 0.5925 | 0.5783 | 0.6872 | 0.7533 | 1 | 0.8419 | 0.6780 | 0.8600 | C6 | 0.3873 | 0.3479 | 0.4494 | 0.5315 | 0.8419 | 1 | 0.8639 | 0.8438 | C7 | 0.2770 | 0.3479 | 0.3014 | 0.3538 | 0.6780 | 0.8639 | 1 | 0.8190 | C8 | 0.5713 | 0.5392 | 0.6358 | 0.7005 | 0.8600 | 0.8438 | 0.8190 | 1 |
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