期刊
MATHEMATICAL PROBLEMS IN ENGINEERING
卷 2015, 期 -, 页码 -出版社
HINDAWI LTD
DOI: 10.1155/2015/348036
关键词
-
资金
- Twelfth Five-Year National Science & Technology Pillar Program [2014BAG01-B04]
- Beijing Science and Technology Plan [Z121100000312101]
This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling methods.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据