GSPM: An Early Detection Approach to Sudden Abnormal Large Outflow in a Metro System
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-2262-4_26
Reference28 articles.
1. Ali, A., et al.: Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction. Neural Netw. 145, 233–247 (2022)
2. Chen, E., et al.: Subway passenger flow prediction for special events using smart card data. IEEE Trans. Intell. Transp. 21(3), 1109–1120 (2019)
3. Chung, J., et al.: Empirical evaluation of gated recurrent neural networks on sequence modeling. In: NIPS 2014
4. Diao, Z., et al.: A hybrid model for short-term traffic volume prediction in massive transportation systems. IEEE Trans. Intell. Transp. 20(3), 935–946 (2018)
5. Fu, X., et al.: Short-term prediction of metro passenger flow with multi-source data: a neural network model fusing spatial and temporal features. Tunn. Undergr. SP Technol. 124, 104486 (2022)
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