首页|Yangzhou University Researchers Describe Findings in Machine Learning (Machine-L earning-Based Prediction of Plant Cuticle-Air Partition Coefficients for Organic Pollutants: Revealing Mechanisms from a Molecular Structure Perspective)
Yangzhou University Researchers Describe Findings in Machine Learning (Machine-L earning-Based Prediction of Plant Cuticle-Air Partition Coefficients for Organic Pollutants: Revealing Mechanisms from a Molecular Structure Perspective)
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 – Researchers detail new data in artific ial intelligence. According to news originating fromYangzhou, People’s Republic of China, by NewsRx correspondents, research stated, “Accurately predictingpla nt cuticle-air partition coefficients (* * K* * [ [ca] ] ) is essential for assessing the eco logical risk oforganic pollutants and elucidating their partitioning mechanisms .”
Yangzhou UniversityYangzhouPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
