【摘要】：近年來,高速鐵路以其快捷、準(zhǔn)時(shí)、安全、環(huán)保的特點(diǎn),在我國乃至世界范圍內(nèi)高速發(fā)展。隨著我國高速鐵路的路網(wǎng)規(guī)模逐步擴(kuò)大和運(yùn)營里程的增加,鐵路旅客運(yùn)輸能力得到逐步釋放,鐵路旅客運(yùn)輸供不應(yīng)求的局面得到緩解,鐵路運(yùn)輸生產(chǎn)正逐步由粗放型向精細(xì)化轉(zhuǎn)換�？土髯鳛殍F路運(yùn)輸組織的基礎(chǔ)和關(guān)鍵因素,其分析工作是一個(gè)復(fù)雜的過程,如何對客流的分布特征及變化規(guī)律進(jìn)行系統(tǒng)分析,掌握客流現(xiàn)狀與變化趨勢,對鐵路開行方案、營銷策略、客票銷售等都具有重要意義。隨著信息化發(fā)展建設(shè)的不斷加深,中國鐵路客票發(fā)售與預(yù)定系統(tǒng)TRS累積了大量、完整、一致的歷史數(shù)據(jù),這可為合理、科學(xué)地分析高速鐵路客流,獲取高質(zhì)量的輔助決策信息提供數(shù)據(jù)基礎(chǔ)。繼物聯(lián)網(wǎng)、云計(jì)算,大數(shù)據(jù)分析技術(shù)成為采集、存儲(chǔ)、管理、分析和共享海量數(shù)據(jù)的核心技術(shù)之一。本文擬采用Microsoft SQL Server 2012作為大數(shù)據(jù)分析工具,構(gòu)建星型模式鐵路客票數(shù)據(jù)倉庫,建立多維數(shù)據(jù)集,進(jìn)行客票數(shù)據(jù)OLAP分析和數(shù)據(jù)挖掘,并將分析和挖掘結(jié)果以規(guī)范的、清晰的報(bào)表等形式可展示給用戶,從而更好的指導(dǎo)鐵路的運(yùn)輸調(diào)配,為領(lǐng)導(dǎo)的決策提供輔助支持。本文首先簡要概括了國內(nèi)外大數(shù)據(jù)和鐵路客流研究現(xiàn)狀以及當(dāng)前大數(shù)據(jù)分析技術(shù)發(fā)展最成熟的數(shù)據(jù)倉庫和數(shù)據(jù)挖掘技術(shù),并根據(jù)高鐵客票的實(shí)際特點(diǎn),詳細(xì)地從旅客出行行為、時(shí)空分布特性、客票收入與運(yùn)能關(guān)系、客流預(yù)測等方面介紹高速鐵路客流分析和挖掘主要研究內(nèi)容;接著探求如何基于Microsoft SQL Server 2012商務(wù)智能工具進(jìn)行高速鐵路客票數(shù)據(jù)倉庫和數(shù)據(jù)挖掘關(guān)鍵技術(shù)開發(fā);最后詳細(xì)介紹高速鐵路客票統(tǒng)計(jì)決策分析系統(tǒng)的開發(fā)工具和具體功能模塊,并采用貴廣高鐵2016.11.21-2016.11.27—周的客票數(shù)據(jù)對高速鐵路客票統(tǒng)計(jì)決策分析系統(tǒng)進(jìn)行測試。
[Abstract]:In recent years, high-speed railway has developed rapidly in our country and even in the world because of its fast, punctual, safe and environmental protection characteristics. With the expansion of China's high-speed railway network and the increase of mileage, the capacity of railway passenger transport has been gradually released, and the situation that the supply of railway passenger transport is in short supply has been alleviated. Railway transportation production is gradually changing from extensive to refined. As the foundation and key factor of railway transportation organization, passenger flow analysis is a complicated process. How to systematically analyze the distribution characteristics and changing law of passenger flow, master the present situation and change trend of passenger flow, and make a plan for railway operation, Marketing strategy, ticket sales and so on are of great significance. With the development of information technology, China Railway ticket selling and booking system (TRS) has accumulated a large amount of complete and consistent historical data, which can be used to analyze the passenger flow of high-speed railway reasonably and scientifically. Access to high-quality decision-making information provides a data base. Following the Internet of things, cloud computing, big data analysis technology has become one of the core technologies for collecting, storing, managing, analyzing and sharing massive data. In this paper, we use Microsoft SQL Server 2012 as big data analysis tool, construct star model railway ticket data warehouse, establish multidimensional data set, carry out OLAP analysis and data mining of ticket data, and standardize the results of analysis and mining. Clear reports and other forms can be displayed to users, so as to better guide the distribution of railway transportation, and provide support for leaders in decision-making. Firstly, this paper briefly summarizes the current research situation of big data and railway passenger flow at home and abroad, and the most mature data warehouse and data mining technology developed by big data analysis technology at present, and according to the actual characteristics of high-speed railway ticket, it makes a detailed analysis of passenger travel behavior. This paper introduces the main research contents of high-speed railway passenger flow analysis and mining in the aspects of space-time distribution characteristics, the relationship between ticket income and transportation capacity, passenger flow prediction and so on. Then it explores how to develop the key technologies of high-speed railway ticket data warehouse and data mining based on Microsoft SQL Server 2012 business intelligence tool. Finally, the development tools and specific function modules of the high speed railway passenger ticket statistics decision analysis system are introduced in detail. The ticket statistics and analysis system of high speed railway is tested by using the ticket data of Gui-Guang high-speed railway during the period of 11. 11. 21-11. 27-week.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U293.13

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