本文選題：交通事故　切入點(diǎn)：司法鑒定　出處：《數(shù)學(xué)的實(shí)踐與認(rèn)識(shí)》2017年08期

【摘要】：道路交通事故鑒定對(duì)于交通事故責(zé)任認(rèn)定和法庭舉證具有重要作用.采集某市近三年125起交通事故案例數(shù)據(jù),建立機(jī)動(dòng)車、自行車、人體總計(jì)73個(gè)調(diào)查變量,運(yùn)用SPSS軟件開展騎推行事故鑒定研究.通過(guò)相關(guān)性分析發(fā)現(xiàn)車座、機(jī)動(dòng)車類型等6個(gè)變量與鑒定結(jié)論相關(guān).開展線性判別分析研究,結(jié)果表明直接對(duì)相關(guān)變量進(jìn)行判別分析可以快速獲得最佳判別效果.當(dāng)函數(shù)選入的自變量為車座時(shí),交叉驗(yàn)證準(zhǔn)確率最高可達(dá)72.8%,說(shuō)明采用數(shù)據(jù)挖掘的方法來(lái)鑒別交通事故中的行為方式具有一定可行性.
[Abstract]:Road traffic accident identification plays an important role in the identification of traffic accident liability and court proof.The data of 125 traffic accidents in a certain city in recent three years were collected, and a total of 73 investigation variables of motor vehicles, bicycles and human bodies were established, and the identification of riding accidents was carried out by using SPSS software.Through the correlation analysis, it is found that six variables, such as vehicle seat and motor vehicle type, are related to the identification conclusion.The results of linear discriminant analysis (LDA) show that the best discriminant effect can be obtained by direct discriminant analysis of related variables.When the independent variable selected by the function is the seat, the accuracy of cross-validation can reach 72.8, which shows that it is feasible to use data mining method to identify the behavior in traffic accidents.
【作者單位】： 北京工業(yè)大學(xué)北京市城市交通運(yùn)行保障研究中心;天津職業(yè)技術(shù)師范大學(xué)天津市交通安全與控制協(xié)同創(chuàng)新中心;北京市交通信息中心;
【基金】：國(guó)家自然科學(xué)基金(61301040) 天津市自然科學(xué)基金重點(diǎn)項(xiàng)目(16JCZDJC38200) 天津職業(yè)技術(shù)師范大學(xué)校級(jí)教學(xué)改革與質(zhì)量建設(shè)研究項(xiàng)目(JGY2015-15)
【分類號(hào)】：U491.31
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本文編號(hào)：1701800