首页|Investigators from Chongqing University of Technology Have Reported New Data on Intelligent Systems (Generalized Spatialtemporal Regression Graph Convolutional Transformer for Traffic Forecasting)
Investigators from Chongqing University of Technology Have Reported New Data on Intelligent Systems (Generalized Spatialtemporal Regression Graph Convolutional Transformer for Traffic Forecasting)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – A new study on Machine Learning - Intelligent Sys tems is now available. According to newsreporting originating in Chongqing, Peo ple’s Republic of China, by NewsRx journalists, research stated,“Spatial-tempor al data is widely available in intelligent transportation systems, and accuratel y solvingnon-stationary of spatial-temporal regression is critical. In most tra ffic flow prediction research, the nonstationarysolution of deep spatial-tempo ral regression tasks is typically formulated as a spatial-temporalgraph modelin g problem.”
ChongqingPeople’s Republic of ChinaA siaIntelligent SystemsMachine LearningTraffic ForecastingTransportationChongqing University of Technology
NETL
NSTL
