Period Division-Based Markov Models for Short-Term Traffic Flow Prediction

Period Division-Based Markov Models for Short-Term Traffic Flow Prediction

Short-term traffic flow prediction is very important and provides the basic data for traffic management and route guidance. The rules of traffic flow data during different periods in a day are different. Thus, this article proposes a membership degree-based Markov (MM) model and two period division-...

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Bibliographic Details
Main Authors: Ronghan Yao, Wensong Zhang, Dong Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Short-term traffic flow
prediction
Markov models
period division
ordered clustering
traffic flow pattern
Online Access:https://ieeexplore.ieee.org/document/9210061/

Internet

https://ieeexplore.ieee.org/document/9210061/

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