Short-term traffic flow prediction plays an important role in route guidance and traffic management. K-NN is considered as one of the most important methods in short-term traffic forecasting, but some disadvantages limit the widespread application. In this paper, we use four tests to find the key factors of the K-NN method, which will give inspires to the further research to improve the method.
Key Factors of K-Nearest Neighbours Nonparametric Regression in Short-Time Traffic Flow Forecasting
Proceedings of the International Conference on Industrial Engineering and Engineering Management
Proceedings of the 21st International Conference on Industrial Engineering and Engineering Management 2014 ; Kapitel : 2 ; 9-12
07.01.2015
4 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Short‐term traffic forecasting using self‐adjusting k‐nearest neighbours
Wiley | 2018
|Short-term traffic forecasting using self-adjusting k-nearest neighbours
IET | 2017
|Composite Nearest Neighbor Nonparametric Regression to Improve Traffic Prediction
Transportation Research Record | 2007
|Composite Nearest Neighbor Nonparametric Regression to Improve Traffic Prediction
Online Contents | 2007
|