Research On Port Freight Operational Risk Control Based On BP Neural Network

Port is the transportation hub for ship in and out safely, and the rally of amphibious transportation. With the development of port and the increasing of throughput, the customer is expand gradually and dispersed. So, the income of port is increasing by years. At the same time, due to lack of understanding credit rating and pay ability, the number of debit customers, amount in arrear and delay payment are increasing and the losses are rising. So, port need to strong the risk control. As the customers are dispersive, complex and large, we need introduce customer classification in risk control. Customer classification has applied in insurance, retail and venture investment and the aim of classification is boost profits and reduce investment risk. The research of port customer classification is incomplete. By analyzing the characteristics of the customer and extract classification indicator, introduce customer classification management, and make corresponding policies to different customers.This research is based on port information construction and customer classification and process optimization, the purpose is control manage risk. In customer classification and risk control, the main research contents are as followings:Firstly, analysis of existing problems and the influence to manage risk. Secondly, based on BP neural network, improve the efficiency of BP. Thirdly, extract classification indicator and construct customer classification model and realize it. Fourthly, apply the classification to risk control and optimize the present process. Analyze the process of contract, business, finance and charge, and design the process optimization. Lastly, realize the process with J2EE technology and the aim of risk control.