Selection of significant On-road sensor data for short-term traffic flow forecasting using the Taguchi method

IEEE Transactions on Industrial Informatics

Volumn 8, Issue 2, 2012, Pages 255-266

  Chan, Kit Yan ^a   Khadem, Saghar ^a   Dillon, Tharam S ^a   Palade, Vasile ^b   Singh, Jaipal ^a   Chang, Elizabeth ^a  

^a CURTIN UNIVERSITY   (Australia)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Input patterns; neural network configuration; neural networks; sensor data; Taguchi method; traffic flow forecasting

Indexed keywords

DEVELOPMENT TIME; HIGH QUALITY; INPUT NODE; INPUT PATTERNS; LEARNING PHASE; NETWORK CONFIGURATION; NEURAL NETWORK MODEL; NEURAL NETWORK PARAMETERS; SENSOR DATA; SHORT-TERM TRAFFIC FLOW; SHORT-TERM TRAFFIC FLOW FORECASTING; SYSTEMATIC OPTIMIZATION; TRAFFIC FLOW; TRAFFIC FLOW FORECASTING; TRIAL AND ERROR; WESTERN AUSTRALIA;

FORECASTING; NEURAL NETWORKS; ROADS AND STREETS; SENSORS; TAGUCHI METHODS;

STREET TRAFFIC CONTROL;

EID: 84859922180     PISSN: 15513203     EISSN: None     Source Type: Journal    
DOI: 10.1109/TII.2011.2179052     Document Type: Article

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