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Traffic Accident Data Mining Using Machine Learning Paradigms

Overview Engineers and researchers in the automobile industry have tried to design and build safer automobiles, but traffic accidents are unavoidable. Patterns involved in dangerous crashes could be detected if they develop a prediction model that automatically classifies the type of injury severity of various traffic accidents. These behavioral and roadway patterns are useful in the development of traffic safety control policy. This paper believes that to obtain the greatest possible accident reduction effects with limited budgetary resources, it is important that measures be based on scientific and objective surveys of the causes of accidents and severity of injuries. This paper presents some models to predict the severity of injury that occurred during traffic accidents using three machine-learning approaches.

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Publisher
Oklahoma State University
File Format
PDF
Date Published
Oct 7, 2008
Format
White Papers
Topics
Artificial Intelligence, Data Mining - Analysis

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