The Risk-Evaluation Model in Customs Based on BP Neural Networks

The basic learning algorithm of BP neural network based on delta learning rule is introduced, and the Levengberg-Marquardt algorithm is described. Then the BP neural network model of risk-evaluation in China Customs is presented. It includes the design of the input layer, the output layer and the hidden layer and the confirmation of the initial weights and the learning rate. On the basis of the data warehouse of risk management of China Customs, The BP neural network of the risk-evaluation is implemented, and the comparison of performance between the momentum factorial algorithm and the Levenberg-Marquardt algorithm is indicated. At last, the further application of BP neural network in China Customs is discussed.