Research On The Port Logistics Capacity Based On Randomforest And Copula

With the rapid development of the global economy, increasing trade between countries create more opportunities for the rapid development of logistics industry. Currently, 90% of goods of international trade is transported through waterway. Port throughput capacity is an important symbol of the port logistics capacity, and also the basis for important decisions. So it's of great significant of accurate forecasting of the port throughput. In this paper, according to the principle of minimum error, through comparison of various forecasting methods such as three exponential smoothing, stochastic gradient Boosting method, neural network and multivariate regression, we finally choose the "entropy-based combination of metabolic Grey Markov forecasting method" to forecast Tianjin Port throughput because of it's effectiveness.Port customer loyalty is the most direct impact factor on port capacity, but customer loyalty can not be observed directly. Therefore, little quantitative study can be found. As the customer's purchase behavior which can be observed directly and loyalty has certain relations of probability. It's consistent with the characteristics of hidden Markov process, so we first use this method to calculate the transfer rules of customer loyalty, then make appropriate strategy to ensure high customer loyalty.There are many factors affecting the port throughput which have different influence. In this paper, we use RandomForest method to study the importance of factors as hinterland economy, social material traffic volume, collecting and distributing system and population. The aim is to find the most important factor, and then analyze the advantages and disadvantages in order to propose concrete solutions to achieve the goal of rapid development of the port.In studying port logistics, the correlation among different materials throughput must be attentioned. And different types of materials, require different handling facilities. This paper uses Copula as the tool of studying correlation of multivariables to study the structure of various materials throughput. As a case about Tianjin Port, the optimal Gumbel Copula function is found. This can help us understand the trend of the various materials throughput, and also guide the handling facilities investment to ensure the port keep in balance and coordinated.