發(fā)布時(shí)間：2019-01-09 13:35

【摘要】：與民航運(yùn)輸相比,鐵路客運(yùn)中不同OD旅客之間在運(yùn)輸能力上的競(jìng)爭(zhēng)較為激烈,尤其是對(duì)我國鐵路客運(yùn)而言。由于我國列車開行距離總體較長且運(yùn)能緊張的問題尚未徹底解決,因而這種矛盾尤為突出。為解決這一矛盾,我國鐵路客運(yùn)部門逐漸形成了一套圍繞票額管理的售票組織策略,用于調(diào)節(jié)列車運(yùn)能對(duì)沿途不同OD旅客需求的滿足程度,其基本原則是:優(yōu)先滿足長途客流,在此基礎(chǔ)上,盡量公平地滿足短途客流。然而,在預(yù)售期開始之前的客流預(yù)測(cè)難以達(dá)到理想的精度,故需要在預(yù)售期內(nèi)根據(jù)售票情況對(duì)有可能存在不合理策略的列車進(jìn)行預(yù)警,以及時(shí)調(diào)整售票組織策略。本文正是圍繞這一問題,試圖提出一種基于分類算法的鐵路客票銷售預(yù)警方法,以克服目前主要依靠管理人員人工判斷的效率低下,不能適應(yīng)近年來列車數(shù)量劇增且運(yùn)營管理需求日益精細(xì)化要求的不足。本文首先對(duì)客票銷售中的售票組織動(dòng)態(tài)調(diào)整及預(yù)警業(yè)務(wù)進(jìn)行了詳細(xì)分析,明確了預(yù)售期內(nèi)客票銷售預(yù)警的業(yè)務(wù)需求。通過對(duì)鐵路客運(yùn)營銷輔助決策系統(tǒng)中列車歷史運(yùn)營數(shù)據(jù)的分析,提出了用于描述列車特征及客票銷售過程特征的屬性變量,并總結(jié)出了五種可能的銷售結(jié)果類型。在此基礎(chǔ)上,結(jié)合貝葉斯分類方法在不確定性推理方面的優(yōu)勢(shì),構(gòu)建了基于貝葉斯分類的客票銷售預(yù)警模型,利用該模型可對(duì)旅客列車客票銷售進(jìn)程進(jìn)行評(píng)估和預(yù)警。論文最后選取了京滬高鐵列車歷史運(yùn)營數(shù)據(jù),通過基于實(shí)際數(shù)據(jù)的仿真實(shí)驗(yàn)驗(yàn)證了所提出的預(yù)警模型及算法的可行性,并對(duì)其預(yù)警結(jié)果準(zhǔn)確度與列車開行日期類型、距離發(fā)車時(shí)間、客座兌現(xiàn)率等因素的關(guān)系進(jìn)行了分析。
[Abstract]:Compared with civil aviation transport, the competition between different OD passengers in railway passenger transport is more fierce, especially for China's railway passenger transport. Because the train running distance is long in our country and the problem of shortage of transportation capacity has not been solved thoroughly, this contradiction is especially prominent. In order to solve this contradiction, the railway passenger transport department of our country has gradually formed a set of ticketing organization strategy around ticket quota management, which is used to adjust the degree of satisfaction of train capacity to different OD passengers along the way. The basic principle is: first to satisfy the long-distance passenger flow. On this basis, as fair as possible to meet the short distance passenger flow. However, the forecast of passenger flow before the pre-sale period is difficult to achieve the ideal precision. Therefore, it is necessary to warn the trains with unreasonable strategies according to the ticket sales situation during the presale period, in order to adjust the ticketing organization strategy in time. This paper attempts to propose an early warning method of railway ticket sales based on classification algorithm to overcome the inefficiency of mainly relying on manual judgment of managers at present. It can not adapt to the shortage of train quantity increasing sharply and operation management demand becoming more and more fine in recent years. In this paper, the dynamic adjustment of ticket sales organization and the early warning business are analyzed in detail, and the business requirements of ticket sales early warning during the pre-sale period are clarified. Based on the analysis of the historical operation data of the railway passenger transport marketing assistant decision system, the attribute variables used to describe the train characteristics and the characteristics of the passenger ticket sales process are put forward, and five possible sales result types are summarized. On this basis, combined with the advantage of Bayesian classification in uncertainty reasoning, a ticket sales early warning model based on Bayesian classification is constructed, which can be used to evaluate and warn passenger train ticket sales process. Finally, the paper selects the historical operation data of Beijing-Shanghai high-speed train, and verifies the feasibility of the proposed early warning model and algorithm through the simulation experiment based on the actual data, and gives the accuracy of the warning results and the type of the train departure date. The relationship between distance departure time, guest rate and other factors is analyzed.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U293.22

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本文編號(hào)：2405694