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Assessment of the Impact of Traffic Police Preventive Interventions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F17%3A00004208" target="_blank" >RIV/46747885:24310/17:00004208 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Assessment of the Impact of Traffic Police Preventive Interventions

  • Original language description

    Free publicly available datasets describing weather and traffic accidents in the Czech Republic have been used for the training of a feed-forward neural network so that it could predict the level of the number of traffic accidents and their cost from weather, weekday, and month. The neural network learns the data for each of the 14 Czech regions separately and also the idea of cross-validation is utilized. The data for each learning task have been separated into Training Set, Development Test Set, and Test Set. Then a statistically significant number of experiments with neural network to get the accuracy of the prediction of the Test Set that happens when the accuracy of the Development Test Set is maximized have been conducted. The aim of the research is to learn whether this methodology can statistically detect any significant difference of the accuracy of prediction between the Test Set formed from days with interventions reported by the Czech Police and the randomly selected Test Set using the assumption that the neural network learns dependencies not affected by preventive interventions.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Mathematical Methods in Economics MME 2017

  • ISBN

    978-80-7435-678-0

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    505-510

  • Publisher name

    Gaudeamus, University of Hradec Králové

  • Place of publication

    Hradec Králové

  • Event location

    Hradec Králové

  • Event date

    Jan 1, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000427151400086