铁路客票数据挖掘系统的设计与实现

发布时间：2018-04-10 02:17

本文选题：铁路　切入点：客票数据　出处：《吉林大学》2015年硕士论文

【摘要】：国家正在大力发展铁路建设,高铁、动车线路全部铺开,铁路建设已经突破以各行政区划分运行界限的模式,形成全国大型的、全面的、统一的铁路网络,到2020年,全国铁路路线将形成京、津、冀9500公里的铁路网和城际铁路的大型交通圈。随着人们生活水平的提高和经济增长,人们对旅行的需求越来越大,因此铁路客运量在逐年的增加,那么如何更为合理、科学的分析铁路客票数据的信息,从而更为有效的、合理的安排客运线路,以及各种铁路资源的合理调配,从而能够确保铁路运行通畅。这是一件十分有意义的事。信息技术迅速发展,大量的数据都可以通过数据库进行存储,但是目前技术还不平衡的是,数据处理功能很低下,所以造成了资源很多却挖掘不到有用的信息,而数据挖掘正是这种时候产生的,是一类从大量数据中提取信息的一种算法、一门科学,它是利用现有的大量的数据来反应目前整个活动的一个发展状况,具体应用在铁路方面就是实时的监控铁路客票的数据,对各种铁路营销指标进行统计和分析,及时为领导的决策提供数据和信息的支持,列车客票销售数据中具有十分丰富的数据,因此,我们需要建立一个智能的数据挖掘系统从这海量的数据中提取出各种有用的信息,并以一种规范的、清晰的报表形式展现给工作人员。这是目前铁路部门亟待解决的一个问题,根据这种情况,本文将建立一个智能的铁路客票分析系统,引入数据挖掘技术到铁路客运系统售票数据进行分析,根据铁路客票的实际特点,对采集的数据进行分析,得出各种影响因素,从而更好的指导铁路的运输调配,改变营销策略。本文首先是阅读了大量的文献,针对国内外数据挖掘的应用情况进行分析,尤其是国内外铁路行业上数据挖掘方法的应用,然后根据我国目前铁路运输的发展状况,总结出数据挖掘方法应用在我国铁路行业的必要性和重大意义,接着分析了数据挖掘技术的理论基础、基本的数据挖掘结构和常用的一些算法,并将本文搭建的铁路客票数据挖掘系统进行介绍,具体介绍该系统采用的工具及该系统的具体功能,最后选择两种最常用的数据挖掘算法——聚类分析和决策树进行原理介绍和铁路客票的实例分析。最后的分析结果表明选择的两种算法可以根据铁路售票数据信息,得出一些知识规则,可以有效的为铁路运行决策者提供信息,例如各类客票的数目的分配,座位类型的调整,某个路线列车数目的配置等等。该铁路客票数据挖掘系统还可以为铁路人员提供各种图表以供分析之用,提高了铁路客票分析的智能化和简洁化。
[Abstract]:The state is vigorously developing railway construction, and all high-speed and high-speed rail lines are being spread out. Railway construction has broken through the model of dividing the operating boundaries among administrative districts, forming a large, comprehensive and unified railway network throughout the country, and by 2020,The national railway route will form Beijing, Tianjin, Hebei 9500 km railway network and intercity railway large traffic circle.With the improvement of people's living standard and economic growth, people's demand for travel is increasing, so railway passenger volume is increasing year by year, so how to analyze the information of railway passenger ticket data more reasonably and scientifically, so as to be more effective.Reasonable arrangement of passenger lines and rational allocation of railway resources can ensure the smooth operation of railways.This is a very meaningful thing.The rapid development of information technology, a large number of data can be stored through the database, but the current technology imbalance is that the data processing function is very low, resulting in a lot of resources but not mining useful information,And data mining is a kind of algorithm that extracts information from a lot of data, a kind of science, which uses a lot of existing data to reflect the current development of the whole activity.The concrete application in the railroad aspect is to monitor the railway ticket data in real time, to carry on the statistics and the analysis to each kind of railway marketing index, to provide the data and the information support for the leader's decision in time,There is a lot of data in train ticket sales data, so we need to build an intelligent data mining system to extract all kinds of useful information from this huge amount of data, and to a standard,A clear report form is presented to the staff.This is an urgent problem to be solved by the railway department. According to this situation, this paper will establish an intelligent railway ticket analysis system and introduce data mining technology to analyze the ticket sales data of the railway passenger transport system.According to the actual characteristics of railway ticket, this paper analyzes the collected data and finds out all kinds of influencing factors, so as to better guide the railway transportation allocation and change the marketing strategy.In this paper, we first read a large number of documents, and analyzed the application of data mining, especially the application of data mining methods in the railway industry, and then according to the current development of railway transportation in China.This paper summarizes the necessity and significance of applying data mining methods in railway industry of our country, and then analyzes the theoretical basis of data mining technology, the basic data mining structure and some commonly used algorithms.The railway ticket data mining system built in this paper is introduced, and the tools used in the system and the specific functions of the system are introduced in detail.Finally, two kinds of most commonly used data mining algorithms, cluster analysis and decision tree, are selected to introduce the principle and analyze the railway passenger ticket.Finally, the analysis results show that the two algorithms can be selected according to the railway ticket data information, get some knowledge rules, can effectively provide information for railway operation decision makers, such as the allocation of various types of tickets, seat type adjustment,Allocation of the number of trains on a route, etc.The railway ticket data mining system can also provide all kinds of charts for railway personnel for analysis, which improves the intelligence and conciseness of railway ticket analysis.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP311.13

【参考文献】