원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.8 No.6
2015.12
pp.303-312
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
It is an important to quickly and accurately forecasting road network traffic flow in intelligent transportation systems, Aiming at the forecasting problem of short-term traffic flow, this paper proposed a traffic flow prediction algorithm, which based on traffic flow sequence partition and neural network model. Firstly, the algorithm divided the traffic flow into different patterns and time sequence by clustering, secondly, described and predicted traffic flow model according to BP neural network. Finally, the experiment shows that based on combined model is much accurate.
목차
Abstract
1. Introduction
2. Traffic Flow Prediction Algorithm
2.1. Traffic Flow Sequence Segmentation
2.2. BP Neural Network Prediction Model
2.3. Combined Model of the Traffic Flow Prediction
3. Experiment Analysis and Results
4. Conclusion
References
1. Introduction
2. Traffic Flow Prediction Algorithm
2.1. Traffic Flow Sequence Segmentation
2.2. BP Neural Network Prediction Model
2.3. Combined Model of the Traffic Flow Prediction
3. Experiment Analysis and Results
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보