首页|Research from Shandong Normal University Provides New Study Findings on Machine Learning (Combining Google traffic map with deep learning model to predict stree t-level traffic-related air pollutants in a complex urban environment)
Research from Shandong Normal University Provides New Study Findings on Machine Learning (Combining Google traffic map with deep learning model to predict stree t-level traffic-related air pollutants in a complex urban environment)
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 Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting originating from Jinan, Peo ple’s Republic of China, by NewsRx correspondents, research stated, “Trafficrel ated air pollution (TRAP) is a major contributor to urban pollution and varies s harply at the street level, posing a challenge for air quality modeling. Traditi onal land use regression models combined with data from fixed monitoring station s may be unable to predict and characterize fine-scale TRAP, especially in compl ex urban environments influenced by various features.”
Shandong Normal UniversityJinanPeopl e’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
