【摘要】：本文致力于道路交通和城市化進(jìn)程對(duì)汽車產(chǎn)業(yè)的影響研究,先定性分析道路交通和城市化進(jìn)程的基本特點(diǎn),探討道路交通、城市進(jìn)程跟汽車產(chǎn)業(yè)之間的關(guān)系,同時(shí)提煉出對(duì)汽車產(chǎn)業(yè)影響的量化因子,定量估算未來(lái)乘用車、商用車及汽車總銷量,最后提出應(yīng)對(duì)措施,并為汽車產(chǎn)業(yè)規(guī)劃部門提供未來(lái)汽車發(fā)展數(shù)據(jù)。 本文通過(guò)查閱國(guó)內(nèi)外有關(guān)資料,了解道路交通、城市化進(jìn)程、汽車產(chǎn)業(yè)的研究現(xiàn)狀和研究基本內(nèi)容,利用個(gè)案研究法、經(jīng)驗(yàn)總結(jié)法、國(guó)內(nèi)外對(duì)比法、等找出它們之間的關(guān)聯(lián)點(diǎn),進(jìn)行道路交通、城市化進(jìn)程跟汽車產(chǎn)業(yè)之間關(guān)系的定性研究,然后結(jié)合我國(guó)具體國(guó)情就關(guān)聯(lián)點(diǎn)提出解決現(xiàn)狀問(wèn)題的有效措施。 本文利用matlab軟件實(shí)現(xiàn)BP神經(jīng)網(wǎng)絡(luò)預(yù)測(cè),利用spss軟件進(jìn)行多元回歸線性預(yù)測(cè),以歷史數(shù)據(jù)為檢測(cè)依據(jù),判斷所建模型的可行性,并對(duì)汽車5～10年末汽車總銷量、乘用車、商用車銷量進(jìn)行了定量預(yù)測(cè)。其模型參數(shù)即道路交通和城市化進(jìn)程對(duì)汽車銷量的影響因素包括城鎮(zhèn)人口數(shù)、城鎮(zhèn)居民人均可支配收入、城市化率、城市年末實(shí)有道路長(zhǎng)度、城市年末實(shí)有道路面積、公路里程。經(jīng)精度檢驗(yàn),兩種模型均可行,BP神經(jīng)網(wǎng)絡(luò)相對(duì)誤差更小些。
[Abstract]:This paper is devoted to the study of the influence of road traffic and urbanization on the automobile industry. Firstly, it qualitatively analyzes the basic characteristics of road traffic and urbanization, and discusses the relationship between road traffic, urban process and automobile industry. At the same time, the quantitative factors affecting the automobile industry are extracted, and the future passenger, commercial and automobile sales volume is estimated quantitatively. Finally, the countermeasures are put forward, and the future automobile development data are provided for the automobile industry planning department. In this paper, by consulting the relevant information at home and abroad, we can find out the relationship between road traffic, urbanization process, automobile industry research status and basic contents, using case study, experience summarization, domestic and foreign comparative methods, etc. The relationship between road traffic, urbanization process and automobile industry is studied qualitatively, and then the effective measures to solve the current situation are put forward according to the actual situation of our country. In this paper, BP neural network prediction is realized by matlab software, multivariate regression linear prediction is carried out by spss software, and the feasibility of the model is judged based on historical data. The volume of commercial vehicles was forecast quantitatively. The model parameters, that is, road traffic and the process of urbanization, affect the sales of cars, including the number of urban population, the per capita disposable income of urban residents, the urbanization rate, the length of roads in cities at the end of the year, and the area of roads in cities at the end of the year. Road mileage The relative error of BP neural network is smaller than that of BP neural network.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F426.471;F512.3

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