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This work aims at unveiling the potential of Transfer Learning (TL) for developing a traffic flow forecasting model in scenarios of absent data.
M. J. Cassidy and R. L. Bertini, “Some traffic features at freeway bottlenecks,” Transportation Research Part B: Methodological , vol. 33, no. 1, pp. 25–42, 1999
1999
Earlier work this paper cites.
S. J. Pan and Q. Yang, “A survey on transfer learning,” IEEE Transactions on Knowledge and Data Engineering , vol. 22, no. 10, pp. 1345–1359, 2009
2009
Earlier work this paper cites.
E. I. Vlahogianni, M. G. Karlaftis, and J. C. Golias, “Short-term traffic forecasting: Where we are and where we’re going,” Transportation Research Part C: Emerging Technologies , vol. 43, pp. 3–19, 2014
2014
Earlier work this paper cites.
Y. Lv, Y. Duan, W. Kang, Z. Li, and F.-Y. Wang, “Traffic flow prediction with big data: a deep learning approach,” IEEE Transactions on Intelligent Transportation Systems , vol. 16, no. 2, pp. 865–873, 2014
2014
Earlier work this paper cites.
P. Zhao, S. C. Hoi, J. Wang, and B. Li, “Online transfer learning,” Artificial Intelligence , vol. 216, pp. 76–102, 2014
2014
Earlier work this paper cites.
C. C. of Madrid. (2014) Madrid open access data. [Online]. Available: https://datos.madrid.es/
2014
Earlier work this paper cites.
J. Lu, V. Behbood, P. Hao, H. Zuo, S. Xue, and G. Zhang, “Transfer learning using computational intelligence: A survey,” Knowledge-Based Systems , vol. 80, pp. 14–23, 2015
2015
Earlier work this paper cites.
X. Niu, Y. Zhu, Q. Cao, X. Zhang, W. Xie, and K. Zheng, “An online-traffic-prediction based route finding mechanism for smart city,” International Journal of Distributed Sensor Networks , vol. 11, no. 8, p. 970256, 2015
2015
Cited alongside, same era.
H.-F. Yang, T. S. Dillon, and Y.-P. P. Chen, “Optimized structure of the traffic flow forecasting model with a deep learning approach,” IEEE Transactions on Neural Networks and Learning Systems , vol. 28, no. 10, pp. 2371–2381, 2016
2016
Cited alongside, same era.
K. Weiss, T. M. Khoshgoftaar, and D. Wang, “A survey of transfer learning,” Journal of Big Data , vol. 3, no. 1, p. 9, 2016
2016
Cited alongside, same era.
Q. Hu, R. Zhang, and Y. Zhou, “Transfer learning for short-term wind speed prediction with deep neural networks,” Renewable Energy , vol. 85, pp. 83–95, 2016
2016
Cited alongside, same era.
H. Yu, Z. Wu, S. Wang, Y. Wang, and X. Ma, “Spatiotemporal recurrent convolutional networks for traffic prediction in transportation networks,” Sensors , vol. 17, no. 7, p. 1501, 2017
2017
Later among the works it cites.
I. Laña, J. Del Ser, M. Velez, and E. I. Vlahogianni, “Road traffic forecasting: Recent advances and new challenges,” IEEE Intelligent Transportation Systems Magazine , vol. 10, no. 2, pp. 93–109, 2018
2018
Later among the works it cites.
H. Yao, F. Wu, J. Ke, X. Tang, Y. Jia, S. Lu, P. Gong, J. Ye, and Z. Li, “Deep multi-view spatial-temporal network for taxi demand prediction,” in AAAI Conference on Artificial Intelligence , 2018
2018
Later among the works it cites.
H. Yao, X. Tang, H. Wei, G. Zheng, and Z. Li, “Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction,” in AAAI Conference on Artificial Intelligence , vol. 33, 2019, pp. 5668–5675
2019
Later among the works it cites.
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I. Laña, J. Del Ser, and I. I. Olabarrieta, “Understanding daily mobility patterns in urban road networks using traffic flow analytics,” in IEEE/IFIP Network Operations and Management Symposium , 2016, pp. 1157–1162
2016
Cited alongside, same era.
Y. Chen, Y. Lv, Z. Li, and F.-Y. Wang, “Long short-term memory model for traffic congestion prediction with online open data,” in IEEE International Conference on Intelligent Transportation Systems , 2016, pp. 132–137
2016
Cited alongside, same era.
Z. Zhao, W. Chen, X. Wu, P. C. Chen, and J. Liu, “LSTM network: a deep learning approach for short-term traffic forecast,” IET Intelligent Transport Systems , vol. 11, no. 2, pp. 68–75, 2017
2017
Cited alongside, same era.
H. Chen, G. Chen, Q. Lu, and L. Peng, “MMSE-based optimized transfer strategy for transfer prediction of parking data,” in IEEE Intelligent Transportation Systems Conference , 2019, pp. 407–412
2019
Later among the works it cites.
M. Seufert, P. Casas, N. Wehner, L. Gang, and K. Li, “Stream-based machine learning for real-time QoE analysis of encrypted video streaming traffic,” in 2019 22nd Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN) . IEEE, 2019, pp. 76–81
2019
Later among the works it cites.