A Container Handling Capacity Prediction Model Based on RBF Neural Networks and Its Simulation

This paper presents a prediction model based on RBF neural network for a type of time-sequence data, and then applies both the RBF model and another BP model to the prediction of container handling capacity in Shanghai port. The result demonstrates that the prediction through RBF model is faster, more exact and better than the BP one on the whole. The RBF neural network model has good prediction ability and practical value for container handling capacity.