Real-time forecasting for short-term traffic flow based on General Regression Neural Network

Proceedings of the World Congress on Intelligent Control and Automation (WCICA)

Volumn , Issue , 2010, Pages 2776-2780

  Kuang, Xianyan ^a,b   Xu, Lunhui ^a   Huang, Yanguo ^a,b   Liu, Fenglei ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b JIANGXI UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Forecasting; GRNN; Short term traffic flow; Time series

Indexed keywords

BASIC THEORY; BP NEURAL NETWORKS; CRITICAL PROBLEMS; DYNAMIC LEARNING; ERROR BACK-PROPAGATION; FORECASTING MODELS; GENERAL REGRESSION NEURAL NETWORK; GRNN; INPUT NEURONS; INTELLIGENT TRANSPORTATION SYSTEMS; REAL-TIME FORECASTING; SEARCH METHOD; SHORT-TERM TRAFFIC FLOW; SHORT-TERM TRAFFIC FLOW FORECASTING; SINGLE-STEP; SMOOTH FACTOR; TRAFFIC FLOW; TRAINING SAMPLE; URBAN ROAD;

BACKPROPAGATION; FORECASTING; INTELLIGENT CONTROL; INTELLIGENT SYSTEMS; NETWORK MANAGEMENT; NEURAL NETWORKS; TIME SERIES; TRAFFIC SURVEYS;

STREET TRAFFIC CONTROL;

EID: 77958139274     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WCICA.2010.5554911     Document Type: Conference Paper

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