【正文】 客貨運(yùn)輸對(duì)該省GDP的影響。我們將其數(shù)據(jù)進(jìn)行整理，分為三大模塊，并分別求和。且該省公路運(yùn)輸業(yè)對(duì)GDP總影響是由這四個(gè)因素加總所得，通過(guò)分析四大因素的百分比的比例，反映公路運(yùn)輸業(yè)對(duì)GDP的影響。且由于分類不精確以及數(shù)據(jù)抽取不客觀等原因，我們?cè)诜治鲈撌」愤\(yùn)輸業(yè)對(duì)GDP的影響時(shí) ，所建立模型難免有不合理之處，在后期我們運(yùn)用EViews綜合求出各抽取元素對(duì)GDP影響的大小，且在分析三個(gè)影響因素時(shí)，已考慮到創(chuàng)造就業(yè)機(jī)會(huì)因素的數(shù)據(jù)不完善，我們將依照這兩方面對(duì)已有調(diào)查項(xiàng)目進(jìn)行調(diào)整，從而達(dá)到提高模型精度的效果。由于附表給出2007年公路建筑投入產(chǎn)出表，我們可以用通過(guò)分析和用MATLAB計(jì)算公路運(yùn)輸業(yè)的感受度系數(shù)和影響力系數(shù)來(lái)比較準(zhǔn)確的得到公路運(yùn)輸業(yè)對(duì)GDP的波及效應(yīng)。2 問(wèn)題的分析一、問(wèn)題的總分析公路運(yùn)輸對(duì)GDP的影響涉及到交通建設(shè)和客貨運(yùn)輸兩個(gè)階段的貢獻(xiàn)，且公路運(yùn)輸對(duì)直接貢獻(xiàn)、波及效果、相關(guān)行業(yè)的直接消費(fèi)和創(chuàng)造就業(yè)機(jī)會(huì)等各方面都會(huì)產(chǎn)生影響。5．問(wèn)題五：原調(diào)查表中所給的調(diào)查項(xiàng)目有些需要分類，有些利用不上的調(diào)查項(xiàng)需要?jiǎng)h除，這樣的調(diào)整可以很大程度地提高模型的精度。3．問(wèn)題三：綜合問(wèn)題一、二的結(jié)論，并通過(guò)建模分析各省每年GDP均值預(yù)測(cè)2012年該省GDP,從而分析該省公路運(yùn)輸業(yè)對(duì)于該省GDP的影響。三、要解決的問(wèn)題1．問(wèn)題一：根據(jù)2012年公路運(yùn)輸調(diào)查數(shù)據(jù)，分析客貨運(yùn)輸對(duì)國(guó)內(nèi)生產(chǎn)總值（GDP）的直接貢獻(xiàn)，對(duì)于相關(guān)行業(yè)的直接消費(fèi)，創(chuàng)造就業(yè)機(jī)會(huì)三個(gè)方面的影響，定量評(píng)估該省客貨運(yùn)輸對(duì)該省GDP的影響。⑷創(chuàng)造就業(yè)機(jī)會(huì)：不僅僅是交通建設(shè)的過(guò)程需要大量的勞動(dòng)力，創(chuàng)造就業(yè)機(jī)會(huì)，對(duì)于⑶中的相關(guān)行業(yè)的興起也會(huì)創(chuàng)造大量的，各式各樣的就業(yè)機(jī)會(huì)。這種波及對(duì)國(guó)民經(jīng)濟(jì)產(chǎn)業(yè)體系的影響，就是產(chǎn)業(yè)波及效果。它不但可反映一個(gè)國(guó)家的經(jīng)濟(jì)表現(xiàn)，還可以反映一國(guó)的國(guó)力與財(cái)富。公路運(yùn)輸業(yè)即指在公路運(yùn)輸?shù)幕A(chǔ)上延伸出的一系列相關(guān)的產(chǎn)業(yè)鏈。因此，公路運(yùn)輸一般即指汽車運(yùn)輸。主要承擔(dān)短途客貨運(yùn)輸。1 問(wèn)題的重述一、背景知識(shí)1．公路運(yùn)輸業(yè)公路運(yùn)輸是在公路上運(yùn)送旅客和貨物的運(yùn)輸方式。s GDP growth rate is applied to in the province. So we improve spread effect model about road transport industry39。s contribution to GDP in direct contribution, spread effect, direct consumption related industries and creation of employment opportunities. And we adjust the original investigation project from the investigation of classified investigation and analysis of a significant influence in order to improve the model accuracy. Finally, we put forward our own opinions about deep extension of models according to model results and the actual.Question one requires the value of three aspects, which are passenger and freight transport direct contribution to GDP, direct consumption related industries and numerical job creation in this province. According to the percentage of passenger and freight transport about three aspects, we can assess every city’s contribution to GDP. By using Excel and Matlab, we can observe every city’s contribution to GDP. The proportion of passenger and freight transport direct contribution is %, The proportion of direct consumption related industries is %.Question two requires study spread effect of Highway construction and transportation and warehousing industry according to the original title of the schedule 2. We can get array, set sensitivity coefficient model and influence coefficient model that decide spread effect. By using Matlab, the sensitivity coefficient of transportation and warehousing industry is , the influence coefficient of transportation and warehousing industry is .In question three, through the original title of the schedule 2, analyze percentage of road transport of passenger and freight transport. Get numerical highway transportation effect on GDP in 2012 through effect of passenger and freight transport of GDP that consists in question one. Then get GDP of the province in 2007 by the original title of the schedule 2. According to China39。整體思路清晰，切入點(diǎn)獨(dú)到，分析全面，特色鮮明。本文最后還對(duì)模型進(jìn)行了誤差分析，利用Matlab對(duì)問(wèn)題三中的該省年均GDP增長(zhǎng)率進(jìn)行了靈敏度分析。針對(duì)問(wèn)題五，本文綜合以上模型，結(jié)合實(shí)際，提出了對(duì)原有的調(diào)查項(xiàng)目合理的分類和刪除，如將原創(chuàng)造就業(yè)機(jī)會(huì)中駕駛員項(xiàng)改進(jìn)為駕駛員工資項(xiàng)，刪除對(duì)計(jì)算GDP無(wú)影響調(diào)查項(xiàng)等。根據(jù)圖形得出只有前兩個(gè)因素對(duì)模型有顯著影響。從而得到2012年公路運(yùn)輸對(duì)該省GDP的貢獻(xiàn)占該省GDP的比例，%。結(jié)合問(wèn)題一中客貨運(yùn)輸對(duì)GDP的影響，通過(guò)原題所附表2分析客貨運(yùn)輸占公路運(yùn)輸?shù)陌俜直龋玫?012年公路運(yùn)輸對(duì)GDP的影響數(shù)值。運(yùn)用Matlab求解。問(wèn)題二要求以原題所附表2中的數(shù)據(jù)作為研究對(duì)象，來(lái)研究公路建筑業(yè)和交通運(yùn)輸及倉(cāng)儲(chǔ)業(yè)的波及效果。由Excel作表和Matlab作圖可看出各市三方面對(duì)GDP的影響。最后，將模型結(jié)果和實(shí)際相結(jié)合，對(duì)模型的深層次推廣提出了自己的意見(jiàn)。參賽隊(duì)號(hào)1560 “認(rèn)證杯”數(shù)學(xué)中國(guó)數(shù)學(xué)建模網(wǎng)絡(luò)挑戰(zhàn)賽題 目 公路運(yùn)輸業(yè)對(duì)于國(guó)內(nèi)生產(chǎn)總值的影響分析模型關(guān) 鍵 詞 公路運(yùn)輸業(yè)；感應(yīng)度系數(shù)；影響力系數(shù)；多元回歸分析法；Matlab； Eviews；靈敏度分析摘 要本文針對(duì)公路運(yùn)輸業(yè)對(duì)GDP影響的問(wèn)題，綜合利用了數(shù)形結(jié)合、多元統(tǒng)計(jì)、離散分析、回歸分析、靈敏度分析方法分別構(gòu)建了GDP比例預(yù)測(cè)、感應(yīng)度系數(shù)、影響力系數(shù)、多元非回歸等模型，使用Excel、Matlab、Eviews軟件，得出了公路運(yùn)輸業(yè)于直接貢獻(xiàn)、波及效果、對(duì)于相關(guān)行業(yè)的直接消費(fèi)和創(chuàng)造就業(yè)機(jī)會(huì)四個(gè)方面對(duì)GDP的貢獻(xiàn)結(jié)果。并從劃分更精確的調(diào)查模塊、分析每項(xiàng)抽取模塊的影響顯著性兩個(gè)方面，對(duì)原有的調(diào)查項(xiàng)目進(jìn)行精確調(diào)整，提高了模型精度。問(wèn)題一要求求出所給省各城市客貨運(yùn)輸對(duì)GDP的直接貢獻(xiàn)、對(duì)于相關(guān)行業(yè)的直接消費(fèi)和創(chuàng)造就業(yè)機(jī)會(huì)三方面的數(shù)值，并求出以上三方面占客貨運(yùn)輸?shù)陌俜直葋?lái)評(píng)估各市對(duì)GDP的影響。%，%。由該表得到矩陣，建立了決定波及效果的感應(yīng)度系數(shù)模型和影響力系數(shù)模型。針對(duì)問(wèn)題三，引入2012年該省客貨運(yùn)輸引起GDP的增長(zhǎng)和2012年公路運(yùn)輸對(duì)GDP的影響概念。再利用上表求得2007年該省GDP總值，根據(jù)我國(guó)每年GDP的增長(zhǎng)率推算出該省2012年的GDP。針對(duì)問(wèn)題四，將直接貢獻(xiàn)表中每個(gè)調(diào)查項(xiàng)作為自變量，直接貢獻(xiàn)對(duì)GDP的影響作為因變量；再將相關(guān)行業(yè)的直接消費(fèi)表中每個(gè)調(diào)查項(xiàng)作為自變量，相關(guān)行業(yè)的直接消費(fèi)作為因變量，建立多元回歸模型，利用Eviews求解，得出每一項(xiàng)的影響顯著性。這在一定程度上提高了模型的精度。這又進(jìn)一步提高了模型的精度。最后，把以07年到12年的全國(guó)GDP增長(zhǎng)率應(yīng)用到該省的不確定因素考慮進(jìn)來(lái)，將公路運(yùn)輸業(yè)對(duì)GDP的波及效果模型進(jìn)行了改進(jìn)；并從地方到全國(guó)、從運(yùn)輸業(yè)相關(guān)于其他產(chǎn)業(yè)和建模方法方面對(duì)模型做出了推廣。參賽密碼 （由組委會(huì)填寫）參賽隊(duì)號(hào): 1560 所選題目: C 題 英文摘要（選填）AbstractThis article aims at the growth of GDP because of Road Transportation uses multiply a lot of method such as bination of number and shape, multivariate statistics, scatter analysis, regression analysis, sensitivity analysis and sets proportional prediction model. The sensitivity coefficient model, influence coefficient model and multiple regression model etc. We can get highway transportation39。s annual GDP growth rate, we reckon GDP of the province in 2012. Get the province highway transportation of GDP of the province accounted for the proportion of GDP contribution in 2012. The proportion is about %.For question four, regard each investigation of direct contribution as variables table. Regard direct contribution of GDP as the dependent variable. Regard each investigation in related industries table consumption directly as variables table. Regard direct consumer related industries as the dependent variable. We can set multiple regression models and use Eviews. Then we get effect of every significant. And we know only the former two factors have significant effect on the model according to the graph. The coefficient of determination of direct contribution is coefficient of determination of related industries is . It improved the accuracy of the model in a certain extent.For question five, this article points out that the original investigation project can be classified and deleted reasonably. For example, The pilot in original create employment opportunities bees wage a driver, delete survey items that doesn’t affect calculation of GDP. It improved the accuracy of the model in a certain extent, too.The model error is analyzed in this article. The annual GDP growth rate of the province that consist in question three are sensitivity analysis by using Matlab. Finally, we think about the uncertain factors about that taking 2007 to 2012 years of the country39。s contribution to GD