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Multi-step passenger demand forecasting is a crucial task in on-demand vehicle sharing services.
Predicting taxi–passenger demand using streaming data
Luis Moreira-Matias, Joao Gama, Michel Ferreira, Joao Mendes-Moreira, and Luis Damas · 2013
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Traffic prediction in a bike-sharing system
Yexin Li, Yu Zheng, Huichu Zhang, and Lei Chen · 2015
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Convolutional lstm network: A machine learning approach for precipitation nowcasting
SHI Xingjian, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Dnn-based prediction model for spatio-temporal data
Junbo Zhang, Yu Zheng, Dekang Qi, Ruiyuan Li, and Xiuwen Yi · 2016
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A framework for passengers demand prediction and recommendation
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Jintao Ke, Hongyu Zheng, Hai Yang, and Xiqun Michael Chen · 2017
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Semi-supervised classification with graph convolutional networks
Passenger demand prediction with cellular footprints
Jing Chu, Kun Qian, Xu Wang, Lina Yao, Fu Xiao, Jianbo Li, Xin Miao, and Zheng Yang · 2018
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Diffusion convolutional recurrent neural network: Data-driven traffic forecasting
Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu · 2018
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Deep multi-view spatial-temporal network for taxi demand prediction
Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, Jieping Ye, and Zhenhui Li · 2018
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Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting
Bing Yu, Haoteng Yin, and Zhanxing Zhu · 2018
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Predicting multi-step citywide passenger demands using attention-based neural networks
Xian Zhou, Yanyan Shen, Yanmin Zhu, and Linpeng Huang · 2018
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