| The Beijing-Tianjin-Hebei region is located in the capital economic circle,including two municipalities and eleven prefecture-level cities,and is the political and economic center of China.The Beijing-Tianjin-Hebei region is developed on the basis of the Beijing-Tianjin-Tangshan industrial base,with a developed three-dimensional transportation network,carrying a large number of cargo transport tasks every year.In recent years,with the development requirements of high quality coordination,the goal of "carbon neutrality,carbon peak" is proposed,and the freight volume is transferred from highway transportation with higher emissions to railway with lower emissions,which has become the primary goal of transportation structure optimization in The Beijing-Tianjin-Hebei region.With the promotion of special lines for industrial and mining enterprises,special lines for port transportation and railway electrification transformation,the task of converting bulk goods to public rail has been basically realized.However,in the face of higher environmental protection requirements,a large number of industrial and mining enterprises shut down production,cutting fuel and coal consumption and other measures directly caused the reduction of transport demand,on the other hand,the beijing-Tianjin-Hebei region is widely distributed railway stations have not been fully utilized,the waste of freight resources.The mismatch between railway supply and demand in The Beijing-Tianjin-Hebei region is further unbalanced,and the railway sector urgently needs to explore potential freight demand and promote the development of rail-highway combined transport.In this paper,based on the above background analysis,using the method of data mining,visualization methods,machine learning,mathematical programming model and the correlative technology,using the source data collected road,analysis the characteristic of freight of the beijing-tianjin-hebei region,determine the position of the public rail transport hub,the types of service area and main transport goods,and forecast the freight volume within the service area.In this paper,the original data are preprocessed and stored in the database.Then,data analysis and visualization methods are used to characterize the characteristics of freight transportation in the Beijing-Tianjin-Hebei region.Then,spatial clustering and time-dimension frequent item set mining are used to find the spatio-temporal aggregation regions of highway freight sources,and place names are matched according to latitude and longitude.Then,the alternative points of railway-rail combined transportation hub are selected from the existing railway hubs,location allocation model is established to solve the location and service area of the hub,and cargo types suitable for railway transportation are screened according to the volume and transportation distance.The highway freight volume that each railway-rail combined transportation pivot point may attract and the carbon emissions thus reduced are estimated.Finally,in order to master the trend of freight volume change around the hub of combined transportation,ARIMA and LSTM are respectively used to predict the hourly freight volume of Qian’an city,and the accuracy of prediction and trend judgment is compared.LSTM’s correct judgment of the trend change of freight volume takes up more than 70%.The conclusion of this paper is helpful for the railway freight department in Beijing Tianjin Hebei region to understand the characteristics of regional freight transportation and promote the transfer of road bulk-cargo to railway... |
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