机译:基于动态转换卷积神经网络的交通需求预测
Beihang Univ Sch Comp Sci & Engn State Key Lab Software Dev Environm SKLSDE Beijing 100191 Peoples R China|Beihang Univ Sch Comp Sci & Engn Beijing Adv Innovat Ctr Big Data & Brain Comp BDB Beijing 100191 Peoples R China;
Beihang Univ Sch Comp Sci & Engn State Key Lab Software Dev Environm SKLSDE Beijing 100191 Peoples R China|Beihang Univ Sch Comp Sci & Engn Beijing Adv Innovat Ctr Big Data & Brain Comp BDB Beijing 100191 Peoples R China;
Beihang Univ Sch Comp Sci & Engn State Key Lab Software Dev Environm SKLSDE Beijing 100191 Peoples R China|Beihang Univ Sch Comp Sci & Engn Beijing Adv Innovat Ctr Big Data & Brain Comp BDB Beijing 100191 Peoples R China;
City Univ Hong Kong Dept Informat Syst Hong Kong Peoples R China;
Beihang Univ Sch Comp Sci & Engn State Key Lab Software Dev Environm SKLSDE Beijing 100191 Peoples R China|Beihang Univ Sch Comp Sci & Engn Beijing Adv Innovat Ctr Big Data & Brain Comp BDB Beijing 100191 Peoples R China;
Beihang Univ Sch Comp Sci & Engn State Key Lab Software Dev Environm SKLSDE Beijing 100191 Peoples R China|Beihang Univ Sch Comp Sci & Engn Beijing Adv Innovat Ctr Big Data & Brain Comp BDB Beijing 100191 Peoples R China;
Convolution; Feature extraction; Spatiotemporal phenomena; Predictive models; Convolutional neural networks; Graphical models; Distribution functions; Traffic demand prediction; spatiotemporal; transition convolution; deep learning;
机译:基于多门控时空卷积神经网络的全市交通流量预测
机译:使用轨迹图案挖掘和经常性卷积神经网络的道路交通状态基于语境的预测
机译:基于自回归综合移动平均卷积神经网络模型的时间序列特征考虑特征的交通指标预测与分类
机译:动态扩散卷积经常性神经网络的交通预测
机译:基于社交网络中子图的链路预测卷积神经网络
机译:使用分子动力学模拟和卷积神经网络的液相酸催化反应速率的快速预测
机译:基于扩散卷积经常性神经网络的网络流量预测