Short-term Prediction of Railway Passenger Flow Based on RBF Neural Network

摘要：

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.

关键词： Railway short-term forecast RBF

作者: Yuanchun HUANG Haize PAN

作者单位: College of Urban Railway Transportation Shanghai University of Engineering Science Shanghai,China

会议类型: 国际会议

会议名称: The Fourth International Joint Conference on Computational Science and Optimization(第四届计算科学与优化国际大会 CSO 2011)

会议地点: 昆明、丽江

会议语种:英文

页码: 594-597

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）