DocumentCode
548224
Title
Short-Term Prediction of Railway Passenger Flow Based on RBF Neural Network
Author
Huang, Yuanchun ; Pan, Haize
Author_Institution
Coll. of Urban Railway Transp., Shanghai Univ. of Eng. Sci., Shanghai, China
fYear
2011
fDate
15-19 April 2011
Firstpage
594
Lastpage
597
Abstract
RBF network has a high degree of accuracy when it functions with complex issues for the functional approach. Because of the structural characteristics of the network, it can learn faster than the conventional BP algorithm. This paper propose a short-term passenger forecasting method based on RBF neural which has the characteristics of the underlying data and short-term forecast requirements.
Keywords
backpropagation; radial basis function networks; railway engineering; transportation; RBF neural network; conventional BP algorithm; railway passenger flow; short term passenger forecasting method; short term prediction; structural characteristics; Artificial neural networks; Biological system modeling; Forecasting; Neurons; Rail transportation; Time series analysis; Training; RBF; Railway; short-term forecast;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
Conference_Location
Yunnan
Print_ISBN
978-1-4244-9712-6
Electronic_ISBN
978-0-7695-4335-2
Type
conf
DOI
10.1109/CSO.2011.240
Filename
5957733
Link To Document