Application of Back Propagation Neural Network on health quarantine based on SAS

Objective To explore the application of Back Propagation Neural Network on health quarantine based on SAS.Methods The Back Propagation Neural Network(BPNN)with the structure of 18 × 5 × 1 was employed for the calculation.A total of 170 vessels with possive exortic vectors and 680 ones with negative vectors were put into the BP neural network.And the messages about new arrival vessels were used for the prediction by the network.Results After one hundred time of iteration,misclassification rate of the training was 0.1647 with the 0.3668 average error;while misclassification rate of the validation was 0.1824 with the 0.4550 average error.The predictive condition was good as the according rate attained 83.3%.Conclusion We can execute the relatively exact prediction based on BP neural network,especially for the highly uncertain nonlinear system.So the network can provide the theoretical base for the risk analysis and alert of health quarantine.