The invention discloses a tunnel traffic accident duration prediction method based on PCA and Adaboost, and the method comprises the following steps: importing historical traffic accident data: carrying out the preprocessing of the data, and dividing the data into a short grade, a medium grade, a long grade and an extra-long grade according to the duration of an accident; carrying out the missing value checking and processing on input variables in the prediction model; and finally, carrying out thermal coding processing on the classification variables. Herein, the PCA method is used for decentralizing original input variables and calculating a covariance matrix of the original input variables, and feature values and feature vectors of the original input variables are calculated on the basis, and a plurality of feature values and corresponding feature vectors are sequentially determined from small to large. Firstly, traffic accident duration is classified based on a weak classifier, and a basic classification result is obtained through sample training; and then, an Adaboost iteration framework is adopted to calculate classification error samples of the weak classifier, the weight of the classification error samples is improved, a next weak classifier is constructed on this basis, and a final strong classifier is obtained after multiple iterations.
本发明公开了一种基于PCA和Adaboost的隧道交通事故持续时间预测方法,包括以下步骤:导入历史交通事故数据:首先对数据进行预处理,根据事故的持续时间划分为短、中、长和特长四个等级;并对预测模型中的输入变量进行缺失值检验和处理;最后对分类变量进行热编码处理。使用PCA方法对原输入变量进行去中心化处理并计算其协方差矩阵,在此基础上计算其特征值和特征向量,从小到大依次确定若干个特征值及相应的特征向量。首先基于弱分类器对交通事故持续时间进行分类,经过对样本的训练得到基础分类结果;然后采用Adaboost迭代框架计算弱分类器的分类错误样本,提高分类错误样本的权值,在此基础上构建下一个弱分类器,多次迭代后得到最终的强分类器。
Tunnel traffic accident duration prediction method based on PCA and Adaboost
一种基于PCA和Adaboost的隧道交通事故持续时间预测方法
2021-08-31
Patent
Electronic Resource
Chinese
IPC: | G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / G06K Erkennen von Daten , RECOGNITION OF DATA / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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