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  • Data Quality Enhancement for Traffic Accident Data

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    Deb_2017_01Thesis.pdf (2.113Mb)
    Author(s)
    Deb, Rupam
    Primary Supervisor
    Liew, Alan
    Other Supervisors
    Wang, Junhu
    Year published
    2017
    Metadata
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    Abstract
    Death, injury, and disability resulting from road traffic crashes continue to be a major global public health problem. Recent data suggest that the number of fatalities from traffic crashes is in excess of 1.25 million people each year with non-fatal injuries affecting a further 20-50 million people. It is predicted that by 2030, road traffic accidents will have progressed to be the 5th leading cause of death and that the number of people who will die annually from traffic accidents will have doubled from current levels. Both developed and developing countries suffer from the consequences of the increase in human population, ...
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    Death, injury, and disability resulting from road traffic crashes continue to be a major global public health problem. Recent data suggest that the number of fatalities from traffic crashes is in excess of 1.25 million people each year with non-fatal injuries affecting a further 20-50 million people. It is predicted that by 2030, road traffic accidents will have progressed to be the 5th leading cause of death and that the number of people who will die annually from traffic accidents will have doubled from current levels. Both developed and developing countries suffer from the consequences of the increase in human population, and consequently, vehicle numbers. Therefore, methods to reduce accident severity are of great interest to traffic agencies and the public at large. To analyze traffic accident factors effectively, a complete traffic accident historical database is needed. Road accident fatality rates depend on many factors, so it is a very challenging task to investigate the dependencies between the attributes because of the many environmental and road accident factors. Missing data and noisy data in the database obscure the discovery of important factors and lead to invalid conclusions.
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    Thesis Type
    Thesis (PhD Doctorate)
    Degree Program
    Doctor of Philosophy (PhD)
    School
    School of Information and Communication Technology
    DOI
    https://doi.org/10.25904/1912/1309
    Copyright Statement
    The author owns the copyright in this thesis, unless stated otherwise.
    Subject
    Traffic accident data
    Data quality
    Traffic accident analysis
    Publication URI
    http://hdl.handle.net/10072/367725
    Collection
    • Theses - Higher Degree by Research

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