A crime prediction model based on spatial and temporal data

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

Abstract


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.

Keywords


Big data; Crime prediction; Machine learning; Deep learning

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References


M. A. Talhaoui, A. Daif, M. Azzouazi, and Y. Oubrahim, “A Gamified Recommendation Framework,” Int. J. Eng., p. 6.

W. L. Perry, B. McInnis, C. C. Price, S. C. Smith, and J. S. Hollywood, Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations. Rand Corporation, 2013.

R. A. Flarence, S. Bethu, V. Sowmya, K. Anusha, and B. S. Babu, “Importance of Supervised Learning in Prediction Analysis,” vol. 6, no. 1, p. 14.

A. Newton and M. Felson, “Editorial: crime patterns in time and space: the dynamics of crime opportunities in urban areas,” Crime Sci., vol. 4, no. 1, p. 11, Jun. 2015.

S. Garnier, J. M. Caplan, and L. W. Kennedy, “Predicting Dynamical Crime Distribution From Environmental and Social Influences,” Front. Appl. Math. Stat., vol. 4, May 2018.

M. Al Boni and M. S. Gerber, “Area-Specific Crime Prediction Models,” in Machine Learning and Applications (ICMLA), 2016 15th IEEE International Conference on, 2016, pp. 671–676.

M. S. Gerber, “Predicting crime using Twitter and kernel density estimation,” Decis. Support Syst., vol. 61, pp. 115–125, 2014.

F. K. Bappee, A. S. Junior, and S. Matwin, “Predicting Crime Using Spatial Features,” ArXiv180304474 Cs, Mar. 2018.

H. Ait El Bour, M. A. Talhaoui, M. Azzouazi, and R. Moulouki, “Crime Prediction in the Era of Big data,” Int. J. Eng. Technol., vol. 7, no. 4.32, pp. 84–86, Dec. 2018.

L. McClendon and N. Meghanathan, “Using Machine Learning Algorithms to Analyze Crime Data,” Mach. Learn. Appl. Int. J., vol. 2, no. 1, pp. 1–12, Mar. 2015.

O. Gursoy and Md. H. Sharif, “Parallel Computing for Artificial Neural Network Training,” Period. Eng. Nat. Sci. PEN, vol. 6, no. 1, p. 1, Jan. 2018.

B. S. Babu, A. Suneetha, G. C. Babu, Y. J. N. Kumar, and G. Karuna, “Medical Disease Prediction using Grey Wolf optimization and Auto Encoder based Recurrent Neural Network,” vol. 6, no. 1, p. 12, 2018.

A. Stec and D. Klabjan, “Forecasting Crime with Deep Learning,” p. 13, 2017.

“Community areas in Chicago,” Wikipedia. 30-Nov-2018.

“City of Chicago | Data Portal | City of Chicago | Data Portal.” [Online]. Available: https://data.cityofchicago.org/. [Accessed: 30-Dec-2018].




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

Creative Commons License
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