Driving Research Of Regional Economy On Shipping Development Based On Big Data

The Yangtze River is the most abundant inland waterway resources of China,but also the level of high-speed economic development of the region along the Yangtze River,but between the economic growth and the freight volume growth is not coordinated development,the two have some contradictions,such as the implementation of the strategy of economic development and the development of the western regions in the upper reaches of Yangtze River brings a strong shipping demand.The upper reaches of the Yangtze River waterway and Yibin Chongqing only grade III,it is difficult to meet the transportation needs,so the solution between the economic development and the coordinated development of freight demand is particularly important.The main work of this paper is as follows:(1)to explain the general situation of the shipping development of the Rhine,Mississippi River and Yangtze River,to compare the laws of economic total and freight throughput,to analyze the relationship between economy and shipping,to study the physical process of economic driven shipping development,and to refer to the correlation of freight demand forecast at home and abroad.Literature,summarize the advantages and disadvantages of various forecasting methods and applicability,laying the groundwork for future research.(2)the goods are classified accurately according to the national classification standards of goods,and the goods are divided into 17 large categories,122 middle classes and 197 small classes.Based on the large data method,the relationship between the economy and the goods is analyzed.The correlation analysis of various factors affecting the output of various kinds of goods is analyzed,and the goods are constructed by multiple regression analysis method.The model of product output and demand.(3)to build an inter regional input-output value table based on the input-output table in 2012,and use the value amount equal to the physical quantity multiplied by the transformation relation of the price,transform the value scale into the physical scale,and compare the relation between the water transport proportion of the Yangtze River economic belt and the waterway depth,and establish the empirical model of the water transportcompetitiveness.In order to complete the simulation study on the allocation of total freight volume to water volume,we constructed an economic driven shipping demand model.(4)the present situation of social economy and comprehensive transportation development in the Yangtze River economic belt is introduced.Based on the model of shipping demand,the water volume forecast of the Yangtze Economic Belt is completed.The main conclusions of this paper are as follows:(1)the model of goods output and demand is constructed based on large data method,which is verified by the data in2015.The results of the goods output and demand model are better.The results show that the big data method is suitable for studying the relationship between supply and demand of goods.(2)the shipping demand model can not only predict the total volume of freight transportation in various regions,but also predict the flow direction between regions.At the same time,it can complete the simulation study of the total freight volume distribution to the water transport volume,and realize the spatial connection of the freight transport.(3)the empirical model of water transport competitiveness established in this paper can more intuitively reflect and quantify the increase of water transport competitiveness caused by the upgrading of the channel grade,and compare the calculated value of the model to the measured value.The results show that the empirical model of the water transport competitiveness is better.The innovation points of this paper are as follows:The model of shipping demand model driven by economy is constructed to predict the freight volume.This model can not only predict the demand of freight transportation in all provinces,but also complete the simulation of cargo demand in various provinces and realize the spatial connection of freight transportation.