高速公路收费稽查系统数据挖掘技术研究
发布时间:2019-02-23 10:23
【摘要】:随着我国高速公路的里程数不断增加,路网规模不断扩大,车辆单次缴纳通行费金额增多,从而导致车主逃费的现象也越来频繁地出现。目前,高速公路收费稽查人员还无法做到使用信息技术处理海量的收费记录数据。通过对偷逃通行费行为以及稽查工作方式的研究可以补充高速公路稽查工作的不足。数据挖掘技术在这一过程中发挥着重要作用,它能够将需要的信息从大量的收费数据中提取出来,并进行归类以及预测。将数据挖掘技术用于高速公路联网收费稽查工作,将会大大提高工作的效率和针对性。 本文以高速公路联网收费稽查的工作内容作为切入点展开研究,对偷逃通行费行为进行了详细的分析。本文将数据挖掘技术引入收费稽查工作中,对关键技术进行了研究。在上述研究基础上,构建了辅助收费稽查工作的系统模型,并结合数据挖掘技术给出了模型应用的实例。结果表明,本模型给出的预测具有较高的准确率,特别是针对换卡、偷换车牌等逃费行为较为敏感。本文对逃费行为和稽查工作的系统分析,以及基于数据挖掘技术对收费稽查工作进行建模,对于稽查工作具有指导意义,能够在实践中促进稽查工作效率的提高,,并提升高速公路运营单位管理水平。
[Abstract]:With the increasing mileage of freeway in our country, the scale of road network is expanding, and the amount of toll paid by vehicle is increasing, which leads to the phenomenon that the owner evades the toll more and more frequently. At present, highway toll inspectors can not use information technology to process massive toll record data. Through the study of the behavior of evading tolls and the way of checking, the deficiency of highway inspection can be supplemented. Data mining technology plays an important role in this process, it can extract the information needed from a large number of fee data, classify and predict. The efficiency and pertinence of the work will be greatly improved when the data mining technology is used in the toll checking work of expressway network. In this paper, the contents of highway network toll audit are taken as the starting point to study the behavior of evading tolls, and the behavior of evading tolls is analyzed in detail. In this paper, the data mining technology is introduced into the charge audit, and the key technology is studied. On the basis of the above research, the system model of auxiliary charge audit is constructed, and an example of application of the model is given in combination with data mining technology. The results show that the prediction given by this model has a high accuracy, especially for card exchange, license plate evasion and other evasion behavior is more sensitive. In this paper, the systematic analysis of fee evasion behavior and audit work, as well as the modeling of fee audit based on data mining technology, is of guiding significance for audit work, and can promote the efficiency of audit work in practice. And improve the highway operation unit management level.
【学位授予单位】:长安大学
【学位级别】:硕士
【学位授予年份】:2014
【分类号】:U495
本文编号:2428728
[Abstract]:With the increasing mileage of freeway in our country, the scale of road network is expanding, and the amount of toll paid by vehicle is increasing, which leads to the phenomenon that the owner evades the toll more and more frequently. At present, highway toll inspectors can not use information technology to process massive toll record data. Through the study of the behavior of evading tolls and the way of checking, the deficiency of highway inspection can be supplemented. Data mining technology plays an important role in this process, it can extract the information needed from a large number of fee data, classify and predict. The efficiency and pertinence of the work will be greatly improved when the data mining technology is used in the toll checking work of expressway network. In this paper, the contents of highway network toll audit are taken as the starting point to study the behavior of evading tolls, and the behavior of evading tolls is analyzed in detail. In this paper, the data mining technology is introduced into the charge audit, and the key technology is studied. On the basis of the above research, the system model of auxiliary charge audit is constructed, and an example of application of the model is given in combination with data mining technology. The results show that the prediction given by this model has a high accuracy, especially for card exchange, license plate evasion and other evasion behavior is more sensitive. In this paper, the systematic analysis of fee evasion behavior and audit work, as well as the modeling of fee audit based on data mining technology, is of guiding significance for audit work, and can promote the efficiency of audit work in practice. And improve the highway operation unit management level.
【学位授予单位】:长安大学
【学位级别】:硕士
【学位授予年份】:2014
【分类号】:U495
【引证文献】
中国期刊全文数据库 前1条
1 赵彦;;ETC卡签在线发行及审核方案探讨[J];公路交通科技(应用技术版);2015年09期
本文编号:2428728
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