文章基本信息

标题：Prediction of Roadway Crashes Using Logistic Regression in SAS
其他标题：English
本地全文：下载
作者：Srinivasan Suresh
期刊名称：International Journal of Computer Science and Engineering
印刷版ISSN：2278-9960
电子版ISSN：2278-9979
出版年度：2020
卷号：7
期号：10
页码：13-17
DOI：10.14445/23488387/IJCSE-V7I10P103
出版社：IASET Journals
摘要：Roadway crashes occur instantly with less time to respond. Predicting these crashes or identifying the major factors affecting these crashes can help to reduce these from occurring. As machine learning techniques help make these predictions and identify the impact factors, they can be applied to the roadway crash data set. The data set is obtained for the State of Virginia from the Department of Transportation. The logistic regression method was applied by grouping the dataset into fatal and non-fatal crashes. The model was built in SAS studio software and had an accuracy of 76%. The major factors were identified as Road, not lighted, Ramps, and Intersections on Divided roadways.
关键词：Fatal roadway crashes; Machine Learning; Logistic Regression; State of Virginia