A novel forecasting approach inspired by human memory: The example of short-term traffic volume forecasting

Transportation Research Part C: Emerging Technologies

Volumn 17, Issue 5, 2009, Pages 510-525

  Huang, Shan ^a   Sadek, Adel W ^a  

^a State University of New York   (United States)

Author keywords

Artificial intelligence; Biologically inspired systems; Memory; Short term traffic prediction; Traffic forecasting

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; BIOMIMETICS; DATA STORAGE EQUIPMENT; HIGHWAY TRAFFIC CONTROL; INTELLIGENT SYSTEMS; NEURAL NETWORKS;

BACK PROPAGATION NEURAL NETWORKS; BIOLOGICALLY INSPIRED SYSTEMS; COMPUTATIONAL REQUIREMENTS; INTELLIGENT TRANSPORTATION SYSTEMS; NEAREST-NEIGHBOR APPROACHES; SHORT-TERM TRAFFIC VOLUME; TRAFFIC FORECASTING; TRAFFIC PREDICTION;

FORECASTING;

ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; DATA SET; FORECASTING METHOD; PREDICTION; TRAFFIC MANAGEMENT;

NORTH AMERICA; UNITED STATES; VIRGINIA;

EID: 67949085060     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trc.2009.04.006     Document Type: Article

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