A Container Handling Prediction Method For Seaports Based On Clustering Ananlysis

With the development of the world economy and trade, the port container handling becomes not only an important sign of judging the station of a port in the international economy and trade, but also a rain glass of the flourishing degree in economy of a country or an area Researching the methods to forecast the container hanging and doing the prediction properly are very important to guide the programming and construction of the ports, to confirm the investment scale of the ports and moreover to accelerate the development of the areas. However, for a long time, the research on the methods to forecast the container handling of port mainly focus on the amelioration of the idiographic forecasting methods, neglecting the otherness of the increasing rule of the port's throughput in different areas, which leads to the port's forecasting error.This paper brings forward a new research method of port container throughput based on the port's cluster analysis. First of all, in the paper, the author introduces the basic theories and models, and especially does the systemic research on time series models, grey models, regression models and RBF neural network model, and moreover brings the grey Markov-chain residual modification model, the grey Fourier residual modification model, the grey model on time series error corrected, GOM model and grey nonlinear model to the port container throughput forecasting for the first time. And then, based on the characteristic of the port's container increasing, the clustering analysis method is applied to classify the major seaports of our country into three types: the normally increasing port, the accelerative increasing port and the fluctuating increasing port. The characteristic of the port's container increasing is also analyzed. Finally, the author applies the time series models, grey models, regression model and RBF neural network model to forecast the container throughput of the three type ports, and gets the conclusion of applicable forecasting methods for special container-port through the comparison and analysis.