發(fā)布時(shí)間：2018-04-10 02:17

  本文選題：鐵路　切入點(diǎn)：客票數(shù)據(jù)　出處：《吉林大學(xué)》2015年碩士論文

【摘要】：國(guó)家正在大力發(fā)展鐵路建設(shè),高鐵、動(dòng)車線路全部鋪開(kāi),鐵路建設(shè)已經(jīng)突破以各行政區(qū)劃分運(yùn)行界限的模式,形成全國(guó)大型的、全面的、統(tǒng)一的鐵路網(wǎng)絡(luò),到2020年,全國(guó)鐵路路線將形成京、津、冀9500公里的鐵路網(wǎng)和城際鐵路的大型交通圈。隨著人們生活水平的提高和經(jīng)濟(jì)增長(zhǎng),人們對(duì)旅行的需求越來(lái)越大,因此鐵路客運(yùn)量在逐年的增加,那么如何更為合理、科學(xué)的分析鐵路客票數(shù)據(jù)的信息,從而更為有效的、合理的安排客運(yùn)線路,以及各種鐵路資源的合理調(diào)配,從而能夠確保鐵路運(yùn)行通暢。這是一件十分有意義的事。信息技術(shù)迅速發(fā)展,大量的數(shù)據(jù)都可以通過(guò)數(shù)據(jù)庫(kù)進(jìn)行存儲(chǔ),但是目前技術(shù)還不平衡的是,數(shù)據(jù)處理功能很低下,所以造成了資源很多卻挖掘不到有用的信息,而數(shù)據(jù)挖掘正是這種時(shí)候產(chǎn)生的,是一類從大量數(shù)據(jù)中提取信息的一種算法、一門科學(xué),它是利用現(xiàn)有的大量的數(shù)據(jù)來(lái)反應(yīng)目前整個(gè)活動(dòng)的一個(gè)發(fā)展?fàn)顩r,具體應(yīng)用在鐵路方面就是實(shí)時(shí)的監(jiān)控鐵路客票的數(shù)據(jù),對(duì)各種鐵路營(yíng)銷指標(biāo)進(jìn)行統(tǒng)計(jì)和分析,及時(shí)為領(lǐng)導(dǎo)的決策提供數(shù)據(jù)和信息的支持,列車客票銷售數(shù)據(jù)中具有十分豐富的數(shù)據(jù),因此,我們需要建立一個(gè)智能的數(shù)據(jù)挖掘系統(tǒng)從這海量的數(shù)據(jù)中提取出各種有用的信息,并以一種規(guī)范的、清晰的報(bào)表形式展現(xiàn)給工作人員。這是目前鐵路部門亟待解決的一個(gè)問(wèn)題,根據(jù)這種情況,本文將建立一個(gè)智能的鐵路客票分析系統(tǒng),引入數(shù)據(jù)挖掘技術(shù)到鐵路客運(yùn)系統(tǒng)售票數(shù)據(jù)進(jìn)行分析,根據(jù)鐵路客票的實(shí)際特點(diǎn),對(duì)采集的數(shù)據(jù)進(jìn)行分析,得出各種影響因素,從而更好的指導(dǎo)鐵路的運(yùn)輸調(diào)配,改變營(yíng)銷策略。本文首先是閱讀了大量的文獻(xiàn),針對(duì)國(guó)內(nèi)外數(shù)據(jù)挖掘的應(yīng)用情況進(jìn)行分析,尤其是國(guó)內(nèi)外鐵路行業(yè)上數(shù)據(jù)挖掘方法的應(yīng)用,然后根據(jù)我國(guó)目前鐵路運(yùn)輸?shù)陌l(fā)展?fàn)顩r,總結(jié)出數(shù)據(jù)挖掘方法應(yīng)用在我國(guó)鐵路行業(yè)的必要性和重大意義,接著分析了數(shù)據(jù)挖掘技術(shù)的理論基礎(chǔ)、基本的數(shù)據(jù)挖掘結(jié)構(gòu)和常用的一些算法,并將本文搭建的鐵路客票數(shù)據(jù)挖掘系統(tǒng)進(jìn)行介紹,具體介紹該系統(tǒng)采用的工具及該系統(tǒng)的具體功能,最后選擇兩種最常用的數(shù)據(jù)挖掘算法——聚類分析和決策樹(shù)進(jìn)行原理介紹和鐵路客票的實(shí)例分析。最后的分析結(jié)果表明選擇的兩種算法可以根據(jù)鐵路售票數(shù)據(jù)信息,得出一些知識(shí)規(guī)則,可以有效的為鐵路運(yùn)行決策者提供信息,例如各類客票的數(shù)目的分配,座位類型的調(diào)整,某個(gè)路線列車數(shù)目的配置等等。該鐵路客票數(shù)據(jù)挖掘系統(tǒng)還可以為鐵路人員提供各種圖表以供分析之用,提高了鐵路客票分析的智能化和簡(jiǎn)潔化。
[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.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP311.13

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