【推荐】（论文+代码+数据）AAAI 2017论文：基于深度学习的城市人流预测

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点击上方 “机器学习研究会” 可以订阅哦 摘要   转自：郑宇MSRA 微软亚洲研究院郑宇博士的AAAI 2017论文《Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction》论文、数据和代码均已公开。 论文摘要： Forecasting the flow of crowds is of great importance to traffic management and public safety, and very challenging as it is affected by many complex factors, such as inter-region traffic, events, and weather. We propose a deep-learning-based approach, called ST-ResNet, to collectively forecast the inflow and outflow of crowds in each and every region of a city. We design an end-to-end structure of ST-ResNet based on unique properties of spatio-temporal data. More specifically, we employ the residual neural network framework to model the temporal closeness, period, and trend properties of crowd traffic ………………………………