Study On Factors Affecting River-Sea Combined Transport And Prediction Method Of Volume

River-sea combined transport is a combination of marine transport and inland transport,using inland vessels to connect marine vessels for transport,or directly using river-sea-direct vessels for transport,which reduces the number of cargo loading and unloading,the loss and transport costs of cargo during the loading and unloading process,and can reduce energy consumption and environmental pollution.Especially in the environment where the country is vigorously promoting energy conservation and emission reduction,road transport is becoming more saturated,and the shipping industry has been in a downturn for a long time,the importance of river-sea combined transport has become increasingly prominent.In order to vigorously develop river-sea combined transport and better promote social progress and development,this paper studies the factors that affect river-sea combined transport and the method of transport volume prediction.The development of river-sea combined transport is influenced by many factors.By analyzing the factors affecting river-sea combined transport in detail,it can provide theoretical support for the development of river-sea combined transport and lay a foundation for the research on the method of river-sea combined transport forecast.In this paper,based on the analysis of the factors affecting river-sea combined transport,some quantifiable factors and their quantitative indicators are selected,and the gray correlation analysis is used to establish the main factors affecting the amount of river-sea combined transport.The prediction of the volume of river-sea combined transport is an important basis for planning the development of river-sea combined transport,and also an important basis for formulating investment and development policies and measures for river-sea combined transport.This paper integrates the multiple sets of influencing factors screened and established by the grey correlation method,and establishes a support vector machine(SVM)model for predicting the combined traffic volume of rivers and seas.This paper uses particle swarm optimization(Particle Swarm Optimization,PSO)to optimize the parameters of the support vector machine,and uses the support vector machine model which is optimized by the particle swarm optimization to realize the integrated prediction of the combined traffic volume of rivers and seas,and it is applied to the prediction of the combined traffic volume of rivers and seas in the Ningbo port area.The results show that the model has a higher degree of fit and prediction accuracy than traditional time series forecasting methods,which enriches the ideas and methods of river-sea combined transport volume prediction and provides a new way to solve the river-sea combined transport volume forecast.It has certain theoretical and practical value.