Network-scale traffic modeling and forecasting with graphical lasso and neural networks

Journal of Transportation Engineering

Volumn 138, Issue 11, 2012, Pages 1358-1367

  Sun, Shiliang ^a   Huang, Rongqing ^a   Gao, Ya ^a  

^a EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

Gaussian process regression (GPR); Graphical lasso (GL); Neural network (NN); Traffic flow forecasting

Indexed keywords

COVARIANCE MATRIX; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); INTELLIGENT SYSTEMS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; INVERSE PROBLEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; POLLUTION CONTROL; REGRESSION ANALYSIS;

GAUSSIAN PROCESS REGRESSION; GRAPHICAL LASSOS; INTELLIGENT TRANSPORTATION SYSTEMS; NEURAL NETWORK (NN); SHORT-TERM TRAFFIC FLOW; SPARSE GRAPHICAL MODELS; SPARSE INVERSE COVARIANCE MATRIXES; TRAFFIC FLOW FORECASTING;

FORECASTING;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BAYESIAN ANALYSIS; COVARIANCE ANALYSIS; FORECASTING METHOD; INTELLIGENT TRANSPORTATION SYSTEM; MATRIX; MODELING; REGRESSION ANALYSIS; TRAFFIC MANAGEMENT;

EID: 84880387876     PISSN: 0733947X     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)TE.1943-5436.0000435     Document Type: Article

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