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Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting.
- Source :
-
Mathematical Problems in Engineering . 9/9/2015, Vol. 2015, p1-7. 7p. - Publication Year :
- 2015
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1024123X
- Volume :
- 2015
- Database :
- Academic Search Index
- Journal :
- Mathematical Problems in Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 109571365
- Full Text :
- https://doi.org/10.1155/2015/348036