摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。据新闻报道来自深圳的报道，由NewsRx Research记者报道声明，“活性B罗明物种(RBS)，如溴原子(Br)和二溴基(Br)是IM溴中有机物转化的重要氧化物种水本研究建立了定量结构-活性关系(QSAR)模型来预测第二代糖尿病基于机器学习(ML)的RBS有序速率常数(k)及RBS间的知识传递并激活氯物种（RCS，如Cl和Cl）以提高模型性能。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting originating from Shenzhen, Pe ople’s Republic of China, by NewsRx correspondents, researchstated, “Reactive b romine species (RBS) such as bromine atom (Br) and dibromine radical (Br) are important oxidative species accounting for the transformation of organic compounds in bromide-containingwater. This study developed quantitative structure-activi ty relationship (QSAR) models to predict secondorder rate constants (k) of RBS by machine learning (ML) and conducted knowledge transfer between RBSand reacti ve chlorine species (RCS, e.g., Cl and Cl) to improve model performance.”
NETL
NSTL