Forecasting Bus Passenger Flow Using Bi-LSTM with Attention Mechanism

Author:

Chen Tao1111,Fang Jie1111,Liu Zhijia1111,Xiao Pinghui1111

Affiliation:

1. College of Civil Engineering, Fuzhou Univ., Fuzhou, P.R. China.

Publisher

American Society of Civil Engineers

Reference16 articles.

1. Application of the ARIMA Models to Urban Roadway Travel Time Prediction: A Case Study;Billings D.;IEEE International Conference on System,2006

2. Using LSTM and GRU neural network methods for traffic flow prediction;Fu R.;IEEE Chinese Association of Automation,2017

3. Harvey A. C. (1990). "Forecasting Structural Time Series Models and the Kalman Filter." Cambridge University U.K.

4. Deep Architecture for Traffic Flow Prediction: Deep Belief Networks With Multitask Learning;Huang W.;IEEE Transactions on Intelligent Transportation Systems,2014

5. Huaxiu. Yao. Xianfeng. Tang. and Hua Wei. (2019) "Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction" arXiv preprint arXiv: 1803.01254.

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