长江中游水路货运需求分析与预测研究

发布时间：2018-03-26 17:04

本文选题：长江中游　切入点：货运需求预测　出处：《武汉理工大学》2013年硕士论文

【摘要】：内河航运在世界货物运输史上一直占有着重要地位,中国拥有一个包含5600多条可通航河流,大约总长度119000千米的内河水运系统,有着200个内河港,是亚洲最发达的内河运输系统。而长江是中国内河航运最重要的一条黄金水道。长江干线是长江流域内各产业要素横向运动最重要的通道,是长江流域经济发展的重要纽带。长江经济带聚集众多资源、人口及产业,是国家总体发展战略格局的核心板块。长江航运发挥着带动沿江经济发展及产业布局的重要作用。随着中部地区的逐渐崛起和产业梯度转移进程的加快,长江中游省市加快了发展；以农产品加工、冶金、石化、汽车和建材等为主的产业带已经在长江中游地区形成。2011年,中游腹地以占长江沿线32%的土地、35%的人口,完成了30%的GDP、25%的实际利用外资,在长江流域经济发展中占据着十分重要的位置。目前,对长江干线的需求分析,主要集中在长江干线全线以及下游航段,针对长江中游航段进行需求分析的文献还很少。分析长江中游水运需求,可以帮助更好的进行中游的航运规划,为衔接长江中游与下游运输,综合发展长江航运助力。本文利用回归模型、指数平滑模型、灰色系统模型、以及基于信息熵的组合预测模型,再结合马尔科夫链,根据长江中游几个主要货种和主要港口不同的特点,对其水路货运量和港口吞吐量进行预测。论文的第二章,界定了长江中游水路货运需求的概念,分析了影响长江中游水路货运需求的因素。论文第三章介绍了长江中游航运发展的现状,以及长江中游三省的产业经济发展现状及其未来的发展趋势,并用线性回归模型、指数平滑模型、ARIMA模型等计量经济学模型,对主要的影响因素进行了预测。论文第四章提出了先利用单项预测方法,然后利用信息熵模型确定单项预测权重,进行组合预测,最后利用马尔科夫链方法进行预测值的修正这样的预测思路。论文第五章按照预测模型和思路,运用基于信息熵的组合预测模型及马尔科夫链修正,预测了长江中游煤炭、金属矿石、建筑材料、石油及其制品几个主要货种的货运量。同时,预测了武汉新港、岳阳港、九江港三个主要港口的主要货种的吞吐量。最后根据预测结果,提出促进长江中游航运发展的建议。
[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.
【学位授予单位】：武汉理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：U695.2;F552

【参考文献】