A crime prediction model based on spatial and temporal data

Hicham Ait El Bour, Soumaya Ounacer, Yassine Elghomari, Houda Jihal, Mohamed Azzouazi


In a world where data has become precious thanks to what we can do with it
like forecasting the future, the fight against crime can also benefit from this
technological trend. In this work, we propose a crime prediction model based
on historical data that we prepare and transform into spatiotemporal data by
crime type, for use in machine learning algorithms and then predict, with
maximum accuracy, the risk of having crimes in a spatiotemporal point in the
city. And in order to have a general model not related to a specific type of
crime, we have described our risk by a vector of n values that represent the
risks by type of crime.


Big data; Crime prediction; Machine learning; Deep learning

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DOI: http://dx.doi.org/10.21533/pen.v6i2.524


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Copyright (c) 2019 HICHAM AIT EL BOUR, Soumia Ounacer, Yassine Elghomari, Houda Jihal, Mohamed Azzouazi

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This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License