Prediction of road accidents: A Bayesian hierarchical approach

Accident Analysis and Prevention

Volumn 51, Issue , 2013, Pages 274-291

  Deublein, Markus ^a   Schubert, Matthias ^b   Adey, Bryan T ^a   Köhler, Jochen ^c   Faber, Michael H ^d  

^a ETH ZURICH   (Switzerland)

^b Matrisk GmbH   (Switzerland)

^c NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

^d TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

Accident prediction; Accident risk modelling; Bayesian Probabilistic Networks; Hierarchical Bayes; Injury accidents; Multivariate regression analysis; Road safety assessment

Indexed keywords

ACCIDENT PREDICTION; ACCIDENT RISKS; BAYESIAN PROBABILISTIC NETWORK; HIERARCHICAL BAYES; INJURY ACCIDENTS; MULTIVARIATE REGRESSION ANALYSIS; ROAD SAFETY;

ALGORITHMS; FORECASTING; HIGHWAY ACCIDENTS; INFERENCE ENGINES; MOTOR TRANSPORTATION; PESTICIDE EFFECTS; PROBABILITY DISTRIBUTIONS; REGRESSION ANALYSIS; ROADS AND STREETS; STATISTICS;

BAYESIAN NETWORKS;

ALGORITHM; ARTICLE; AUSTRIA; BAYES THEOREM; EVALUATION; HUMAN; INJURY; INJURY SCALE; MULTIVARIATE ANALYSIS; POISSON DISTRIBUTION; REGRESSION ANALYSIS; RISK ASSESSMENT; SAFETY; STATISTICAL MODEL; STATISTICS; TRAFFIC ACCIDENT;

ACCIDENTS, TRAFFIC; ALGORITHMS; AUSTRIA; BAYES THEOREM; HUMANS; LIKELIHOOD FUNCTIONS; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; POISSON DISTRIBUTION; REGRESSION ANALYSIS; RISK ASSESSMENT; SAFETY; TRAUMA SEVERITY INDICES; WOUNDS AND INJURIES;

MLCS; MLOWN;

EID: 84872056077     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2012.11.019     Document Type: Article

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