基于KNN算法的事故预测

A. M, A. K, Amrutha K, A. M, Chandanashree K R
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引用次数: 0

摘要

今天,政府的首要任务之一是安全。鉴于这一主题的重要性,确定道路交通事故的原因已成为减少交通事故造成的损害的首要目标。机器学习和数据挖掘概念被用来识别影响道路事故及其严重程度的各种因素。该应用程序使用奇数机器学习算法,包括k -最近邻,决策树,随机森林等,根据各种参数进行预测,在所有这些模型中,KNN给出了最好的精度。这些信息可以用来分析未来的输入,提高系统的输出精度。这种模式可以进一步改进,以便将事故报告发送给适当的当局,如医院、救护车和保险公司,因此可以在减少该国的事故死亡率方面非常有用。
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Accident Prediction Using KNN Algorithm
Today, one of the top priorities of governments istrafficsafety. Given the importance of the subject, identifying the causes of road accidents has become the primary goal in reducing the damage caused by traffic accidents. Machine learning and data mining concepts are usedto recognize the various factors that influence road accidents andtheir severity. The application uses at odd Machine Learning algorithms which includes K-Nearest-Neighbor, Decision tree, Random forest, etc make predictions based on various parameters, within allthese models KNN gives the best accuracy. This informationcan be used to analyze future inputs and improve the system'soutput accuracy. This model can be improved further to send the accident report to the appropriate authorities, such as hospitals, ambulances, and insurance companies, and can thus be very useful in reducing accident fatality rates in the country.
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