本文關(guān)鍵詞： 城市出租汽車 運(yùn)營(yíng)博弈策略 數(shù)量投放模型 Logistic模型 神經(jīng)網(wǎng)絡(luò)算法　出處：《中南大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：作為媒體最為關(guān)注、民間改革呼聲最高、主管部門最為頭疼的公共管理政策之一——城市出租汽車數(shù)量管制政策,歷來(lái)爭(zhēng)議不斷。本文應(yīng)用產(chǎn)業(yè)組織、公地悲劇模型、博弈論、神經(jīng)網(wǎng)絡(luò)等理論來(lái)探索城市出租汽車數(shù)量投放的控制,所做的主要工作如下： (1)分析城市出租汽車服務(wù)分類、管制內(nèi)容、行業(yè)模式；剖析北京市近30年來(lái)出租汽車行業(yè)的發(fā)展,總結(jié)出租汽車行業(yè)發(fā)展的四個(gè)階段,明確出租汽車行業(yè)發(fā)展過(guò)程中資本與政策的作用； (2)結(jié)合出租汽車巡游服務(wù)市場(chǎng)的特點(diǎn),構(gòu)建城市出租汽車運(yùn)營(yíng)博弈模型,推導(dǎo)單寡頭、雙寡頭、多寡頭運(yùn)營(yíng)競(jìng)爭(zhēng)下的博弈結(jié)果； (3)總結(jié)出租汽車運(yùn)力調(diào)控指標(biāo)、投放流程和運(yùn)力新增方案的內(nèi)容,從需求、供應(yīng)、競(jìng)爭(zhēng)三個(gè)維度梳理出租汽車數(shù)量投放的影響因素,建立自回歸、Logistic和神經(jīng)網(wǎng)絡(luò)等出租汽車數(shù)量投放模型； (4)利用關(guān)聯(lián)度理論設(shè)計(jì)指標(biāo)篩選方法；對(duì)出租汽車數(shù)量投放進(jìn)行實(shí)例分析,闡明各模型的適用情況；并用BP神經(jīng)網(wǎng)絡(luò)模型對(duì)未來(lái)出租汽車數(shù)量進(jìn)行預(yù)測(cè)； (5)分析現(xiàn)有城市出租汽車數(shù)量管制存在的問(wèn)題,提出縮短調(diào)控周期,動(dòng)態(tài)調(diào)節(jié)運(yùn)力；放開(kāi)約租市場(chǎng),支持技術(shù)創(chuàng)新兩項(xiàng)策略措施。
[Abstract]:As the most concerned by the media, one of the most popular public management policies in charge, the urban taxi quantity control policy, has always been controversial. This paper applies the industrial organization, the tragedy model of the Commons, the game theory. Neural networks and other theories to explore the number of urban taxi delivery control, the main work done as follows:. 1) analyzing the classification, control content, industry pattern of urban taxi service, the development of taxi industry in Beijing in the past 30 years, and summarizing the four stages of the development of taxi industry. Clarify the role of capital and policy in the development of taxi industry; (2) combined with the characteristics of taxi tour service market, this paper constructs a game model of urban taxi operation, and deduces the game results under the competition of oligopoly, duopoly and multi-oligopoly. (3) summing up the indexes of taxi capacity regulation and control, the delivery process and the contents of the new scheme, and combing the influencing factors of taxi quantity from three dimensions: demand, supply and competition. The models of taxi quantity such as logistic regression and neural network were established. (4) designing index screening method by using the theory of correlation degree, analyzing the application of each model and forecasting the number of taxi in the future with BP neural network model. 5) analyzing the problems existing in the quantity control of urban taxi, and putting forward two measures: shortening the control period, dynamically regulating the transportation capacity, opening up the rental market and supporting the technological innovation.
【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：U492.434

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