使用数据挖掘技术预测道路上的事故原因和事故易发位置

Gagandeep Kaur, Er. Harpreet Kaur
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引用次数: 19

摘要

道路交通事故是构成重大损失的创伤性事件的具体实例。数据挖掘工具和技术用于预测事故发生的可能性和事故易发地点。本文通过使用R工具根据事故类型和地点类型估计事故的严重程度,阐明了预测道路上事故的概率,特别是国家公路(SHs)和普通地区公路(odr)。指出道路交通碰撞数据,运用相关分析和探索性可视化技术对道路交通碰撞频率进行分析。最后,提出了道路交通事故的分析方法。运用该方法,可以有效地提高道路交通安全管理的水平和程度。本研究模拟了从交通数据和与建筑行业有关的数据中收集的事故和事件数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of the cause of accident and accident prone location on roads using data mining techniques
Road Accident is a specific instance of traumatic events that constitute major loss. Data mining tools and techniques are used to predict the likelihood of accident and accident prone locations. This paper sheds light on predicting the probability of accidents on roads with special emphasis on STATE HIGHWAYS (SHs) and ORDINARY DISTRICT ROADS (ODRs) by estimating the severity of accidents based on the type of accident, type of spot using the R tool. Pointing out the traffic collision data of roads the frequency of traffic collision of roads is analyzed using correlation analysis and exploratory visualization techniques. Finally, methodology has been proposed to analyze road traffic accidents. Using this methodology, improvement can be promised at the level and extent of road traffic safety management effectively and efficiently. The present study modeled accident and incident data gathered from the traffic data and data related to construction sectors.
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