首页|New Machine Learning Findings from Harbin Institute of Technology Outlined (All-weather Precipitable Water Vapor Map Reconstruction Using Data Fusion and Machine Learning-based Spatial Downscaling)
New Machine Learning Findings from Harbin Institute of Technology Outlined (All-weather Precipitable Water Vapor Map Reconstruction Using Data Fusion and Machine Learning-based Spatial Downscaling)
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 Daily News – Current study results on Machine Learning have been published. According to newsoriginating from Shenzhen, People’s Republic of China, by NewsRx correspondents, research stated, “Precipitablewater vapor (PWV) detection with high spatial resolution and high accuracy is of significantimportance for contributing to extreme weather events monitoring and forecasting. Current PWV products,however, suffer from limitations of spatial and temporal discontinuities, low accuracy, and coarsespatial resolution.”
ShenzhenPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningHarbin Institute of Technology