摘要
由一名新闻记者兼机器人与机器学习每日新闻编辑-研究人员详细介绍了机器学习的新数据。根据News Rx记者源于埃及亚历山大市的新闻报道，研究称："这项研究探索了机器学习模型，以深入了解姆巴拉拉（0.60度S，30.74度E）和基加利（1.94度S，30.09度E）大地接收RS上电离层不规则的动态。采用了为期七年的总电子含量指数(ROTI)数据库和两种建模方法（多变量和单变量）。"
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting originating in Alexandria, Egypt, by News Rx journalists, research stated, “This study explores machine learning models to gain insights into dynamics of ionospheric irregularities over geodetic receive rs in Mbarara (0.60 degrees S, 30.74 degrees E) and Kigali (1.94 degrees S, 30.0 9 degrees E). A seven-year rate of total electron content index (ROTI) database and two modeling approaches (multivariate and univariate) were employed.”
NETL
NSTL