Novel Multi Input Parameter Time Delay Neural Network Model for Traffic Flow Prediction

被引:0
作者
Abhishek, Kumar [1 ]
机构
[1] Silicon Inst Technol, Comp Sci & Engn, Bhubaneswar, Orissa, India
来源
PROCEEDINGS OF 2016 ONLINE INTERNATIONAL CONFERENCE ON GREEN ENGINEERING AND TECHNOLOGIES (IC-GET) | 2016年
关键词
short term traffic flow prediction; Time Delay Neural Network; Multi input parameters;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Intelligent Transportation Systems are an important aspect of our life and are going to become ubiquitous in the near future. Traffic flow prediction is a key component of any Intelligent Transportation Systems. This report uses Artificial Neural Network based models to predict short term traffic flow. Two new input parameters; temperature and truck flow has been introduced into a multi input parameters model. Accordingly five models have been developed based on different combination of the input parameters. By considering past values of multiple input parameters as compared to past values of traffic flow only, the percentage reduction in RMSE values ranges from four to nineteen percentages. Hence, it is suggested to use multi input parameter models for predicting short term traffic flow.
引用
收藏
页数:6
相关论文
共 18 条