本文選題：長(zhǎng)江中游　切入點(diǎn)：貨運(yùn)需求預(yù)測(cè)　出處：《武漢理工大學(xué)》2013年碩士論文

【摘要】：內(nèi)河航運(yùn)在世界貨物運(yùn)輸史上一直占有著重要地位,中國(guó)擁有一個(gè)包含5600多條可通航河流,大約總長(zhǎng)度119000千米的內(nèi)河水運(yùn)系統(tǒng),有著200個(gè)內(nèi)河港,是亞洲最發(fā)達(dá)的內(nèi)河運(yùn)輸系統(tǒng)。而長(zhǎng)江是中國(guó)內(nèi)河航運(yùn)最重要的一條黃金水道。長(zhǎng)江干線是長(zhǎng)江流域內(nèi)各產(chǎn)業(yè)要素橫向運(yùn)動(dòng)最重要的通道,是長(zhǎng)江流域經(jīng)濟(jì)發(fā)展的重要紐帶。長(zhǎng)江經(jīng)濟(jì)帶聚集眾多資源、人口及產(chǎn)業(yè),是國(guó)家總體發(fā)展戰(zhàn)略格局的核心板塊。長(zhǎng)江航運(yùn)發(fā)揮著帶動(dòng)沿江經(jīng)濟(jì)發(fā)展及產(chǎn)業(yè)布局的重要作用。隨著中部地區(qū)的逐漸崛起和產(chǎn)業(yè)梯度轉(zhuǎn)移進(jìn)程的加快,長(zhǎng)江中游省市加快了發(fā)展；以農(nóng)產(chǎn)品加工、冶金、石化、汽車和建材等為主的產(chǎn)業(yè)帶已經(jīng)在長(zhǎng)江中游地區(qū)形成。2011年,中游腹地以占長(zhǎng)江沿線32%的土地、35%的人口,完成了30%的GDP、25%的實(shí)際利用外資,在長(zhǎng)江流域經(jīng)濟(jì)發(fā)展中占據(jù)著十分重要的位置。目前,對(duì)長(zhǎng)江干線的需求分析,主要集中在長(zhǎng)江干線全線以及下游航段,針對(duì)長(zhǎng)江中游航段進(jìn)行需求分析的文獻(xiàn)還很少。分析長(zhǎng)江中游水運(yùn)需求,可以幫助更好的進(jìn)行中游的航運(yùn)規(guī)劃,為銜接長(zhǎng)江中游與下游運(yùn)輸,綜合發(fā)展長(zhǎng)江航運(yùn)助力。 本文利用回歸模型、指數(shù)平滑模型、灰色系統(tǒng)模型、以及基于信息熵的組合預(yù)測(cè)模型,再結(jié)合馬爾科夫鏈,根據(jù)長(zhǎng)江中游幾個(gè)主要貨種和主要港口不同的特點(diǎn),對(duì)其水路貨運(yùn)量和港口吞吐量進(jìn)行預(yù)測(cè)。論文的第二章,界定了長(zhǎng)江中游水路貨運(yùn)需求的概念,分析了影響長(zhǎng)江中游水路貨運(yùn)需求的因素。論文第三章介紹了長(zhǎng)江中游航運(yùn)發(fā)展的現(xiàn)狀,以及長(zhǎng)江中游三省的產(chǎn)業(yè)經(jīng)濟(jì)發(fā)展現(xiàn)狀及其未來(lái)的發(fā)展趨勢(shì),并用線性回歸模型、指數(shù)平滑模型、ARIMA模型等計(jì)量經(jīng)濟(jì)學(xué)模型,對(duì)主要的影響因素進(jìn)行了預(yù)測(cè)。論文第四章提出了先利用單項(xiàng)預(yù)測(cè)方法,然后利用信息熵模型確定單項(xiàng)預(yù)測(cè)權(quán)重,進(jìn)行組合預(yù)測(cè),最后利用馬爾科夫鏈方法進(jìn)行預(yù)測(cè)值的修正這樣的預(yù)測(cè)思路。論文第五章按照預(yù)測(cè)模型和思路,運(yùn)用基于信息熵的組合預(yù)測(cè)模型及馬爾科夫鏈修正,預(yù)測(cè)了長(zhǎng)江中游煤炭、金屬礦石、建筑材料、石油及其制品幾個(gè)主要貨種的貨運(yùn)量。同時(shí),預(yù)測(cè)了武漢新港、岳陽(yáng)港、九江港三個(gè)主要港口的主要貨種的吞吐量。最后根據(jù)預(yù)測(cè)結(jié)果,提出促進(jìn)長(zhǎng)江中游航運(yùn)發(fā)展的建議。
[Abstract]:Inland river shipping has always played an important role in the history of world cargo transportation. China has a inland waterway transportation system consisting of more than 5600 navigable rivers with a total length of about 119000 kilometers and 200 inland ports. It is the most developed inland river transportation system in Asia, and the Yangtze River is the most important golden waterway for inland navigation in China. The main line of the Yangtze River is the most important channel for the horizontal movement of various industrial elements in the Yangtze River Basin. It is an important link in the economic development of the Yangtze River valley. The Yangtze River economic belt gathers a large number of resources, population and industries. Yangtze River shipping plays an important role in promoting the economic development and industrial distribution along the Yangtze River. With the gradual rise of the central region and the acceleration of the process of industrial gradient transfer, Provinces and cities in the middle reaches of the Yangtze River have speeded up their development; industrial belts, dominated by agricultural products processing, metallurgy, petrochemicals, automobiles and building materials, have been formed in the middle reaches of the Yangtze River. In 2011, the hinterland in the middle reaches of the Yangtze River accounted for 32 percent of the land, or 35 percent of the population, along the Yangtze River. It has completed 30% of GDP and 25% of the actual utilization of foreign capital, which occupies a very important position in the economic development of the Yangtze River basin. At present, the demand analysis of the main line of the Yangtze River is mainly focused on the whole line of the main line of the Yangtze River and the lower reaches of the Yangtze River. Analysis of the demand for water transportation in the middle reaches of the Yangtze River is still rare. The analysis of the demand for water transportation in the middle reaches of the Yangtze River can help to better carry out the shipping planning in the middle reaches of the Yangtze River, to link the middle and lower reaches of the Yangtze River, and to comprehensively develop the Yangtze River shipping. In this paper, regression model, exponential smoothing model, grey system model, combined forecasting model based on information entropy and Markov chain are used according to the different characteristics of several main cargo types and main ports in the middle reaches of the Yangtze River. The second chapter defines the concept of waterway freight demand in the middle reaches of the Yangtze River. This paper analyzes the factors that affect the demand of waterway freight in the middle reaches of the Yangtze River. Chapter three introduces the present situation of shipping development in the middle reaches of the Yangtze River, the present situation of the industrial economy development and the future development trend of the three provinces in the middle reaches of the Yangtze River, and uses the linear regression model. The exponential smoothing model, Arima model and other econometric models are used to predict the main influencing factors. In the fourth chapter, the method of single item prediction is proposed, and then the information entropy model is used to determine the weight of single prediction, and then the combined prediction is carried out. In the fifth chapter, according to the forecasting model and train of thought, the combined forecasting model based on information entropy and Markov chain correction are used to predict coal in the middle reaches of the Yangtze River. At the same time, the throughput of the three main ports of Wuhan Xingang, Yueyang Port and Jiujiang Port is predicted. Finally, according to the forecast results, Some suggestions are put forward to promote the development of shipping in the middle reaches of the Yangtze River.
【學(xué)位授予單位】：武漢理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：U695.2;F552

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 馬運(yùn);運(yùn)輸需求的特性及其分析特點(diǎn)[J];北方交通大學(xué)學(xué)報(bào);1994年03期

2 黎偉;陳義華;;基于四階段法的交通需求預(yù)測(cè)組合模型[J];重慶工學(xué)院學(xué)報(bào)(自然科學(xué)版);2007年03期

3 印凡成;王滕滕;黃健元;;基于Gompertz曲線和三次指數(shù)平滑法的貨運(yùn)量組合預(yù)測(cè)[J];大連交通大學(xué)學(xué)報(bào);2012年02期

4 陳淑燕,王煒;交通量的灰色神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)方法[J];東南大學(xué)學(xué)報(bào)(自然科學(xué)版);2004年04期

5 魏仁輝;王靜;;基于因子分析法的區(qū)域公路貨運(yùn)需求分析研究[J];貴州大學(xué)學(xué)報(bào)(自然科學(xué)版);2012年03期

6 曾嘉;曲安琪;鄭丹;;基于雙對(duì)數(shù)模型的貨物運(yùn)輸需求分析[J];中國(guó)科技投資;2012年24期

7 �；�;;四階段法交通需求預(yù)測(cè)的局限與非集計(jì)模型的發(fā)展[J];交通標(biāo)準(zhǔn)化;2007年12期

8 王宇,劉小健,董元?jiǎng)?基于MATLAB的ANFIS網(wǎng)絡(luò)在水運(yùn)貨運(yùn)量預(yù)測(cè)中的應(yīng)用[J];武漢理工大學(xué)學(xué)報(bào)(交通科學(xué)與工程版);2004年04期

9 萬(wàn)軼凌;朱士東;;組合預(yù)測(cè)在水路貨運(yùn)量預(yù)測(cè)中的應(yīng)用[J];交通與運(yùn)輸(學(xué)術(shù)版);2006年02期

10 雷斌;陶海龍;徐曉光;;基于改進(jìn)粒子群優(yōu)化算法的灰色神經(jīng)網(wǎng)絡(luò)的鐵路貨運(yùn)量預(yù)測(cè)[J];計(jì)算機(jī)應(yīng)用;2012年10期

，

本文編號(hào)：1668764