원문정보
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
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.
목차
Abstract
1. Introduction
2. Forecasting Models
2.1. Support Vector Regression
2.2. GA-Based Feature Selection and Parameters Optimization of SVR Models
3. Conclusion and Discussion
References
1. Introduction
2. Forecasting Models
2.1. Support Vector Regression
2.2. GA-Based Feature Selection and Parameters Optimization of SVR Models
3. Conclusion and Discussion
References
저자정보
참고문헌
자료제공 : 네이버학술정보