所属单位：人工智能学院
教研室：智能信息工程系
发表刊物：SN Applied Sciences
刊物所在地：Switzerland AG
项目来源：国家自然基金，华为基金
关键字：vertical positioning,data correction, parameter estimation,multinomial logistic regression,SVM
摘要：In this paper, a method of improving vertical positioning accuracy with the Global Positioning System (GPS) information and barometric pressure values is proposed. First, we clear null values for the raw data collected in various environments, and use the 3$\sigma$-rule to identify outliers. Secondly, the Weighted Multinomial Logistic Regression (WMLR) classifier is trained to obtain the predicted altitude of outliers. The numerical results show that the vertical positioning accuracy is improved from 5.9 meters (the MLR method), 5.4 meters (the SVM method) to 5 . meters (the WMLR).
论文类型：期刊论文
第一作者：姚一炎
通讯作者：罗新龙
论文编号：1445
学科门类：工学
一级学科：计算机科学与技术*
文献类型：J
卷号：2
期号：8
页面范围：1-8
ISSN号：2523-3971
是否译文：否
发表时间：2020-08-01