Authors:
Li Jing
;
Gao Yue
and
Fan Yuhang
Affiliation:
School of Economics and Management and Beijing Jiaotong University, China
Keyword(s):
BP Neural network, High-speed railway, Passenger travel, Environmental factors.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Behavior Study in ITS
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Network Software and Applications
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
As a newly developing mode of transportation, high-speed railway is expanding its influences on national economy and social life. At present, domestic research on high-speed railway mostly focus on tech level, no systematic and comprehensive research have been done to the aspect of passenger travel. This study taking uses of Matlab 6.6 concentrates on environmental factors’ effects on travel choices of High-speed railway passengers, building up a forecast model based on BP Artificial Neural network. Through the comparison and analysis of predicted and real data, effectiveness of this method is proved.