GA-Support Vector Regression Based Ship Traffic Flow Prediction

Abstract

The observation and forecasting of vessel traffic flow is the foundmental of design for ships’ routeing system. An integrated Genetic Algorithm (GA) based Support Vector Machine (SVM) model for vessel traffic flow forecasting with input factors selection procession is presented in this paper. GA based SVM forecasting model is established whose parameters were optimized through genetic algorithms. Finally, the prediction model is used for ningbo-zhoushan port and the prediction result shows that the improved model reflects the actual growth of vessel traffic flow trend more reasonable and effectively.