The entire drug trafficking database of the London Metropolitan Police Department comprising 144 variables and some 1,120 records representing arrests for illegal drug activities in the 32 boroughs of London was analyzed utilizing the constraint satisfaction (CS) artificial neural network (ANN) method developed in the previous chapter. A detailed analysis of the resulting analysis has shown each area of London and their drug activities, associated drug felons and suspects, and profile of activity that can be used to guide police in focusing their limited manpower into areas and kinds of individuals most characteristic of association with certain crimes. By utilizing these methods, profiling has been lifted from an arguably subjective mode to one objectively determined by sophisticated mathematical means and represented in the CS ANNs.
CITATION STYLE
Intraligi, M., & Buscema, M. (2014). Application of the constraint satisfaction network. In Intelligent Data Mining in Law Enforcement Analytics: New Neural Networks Applied to Real Problems (pp. 231–313). Springer Netherlands. https://doi.org/10.1007/978-94-007-4914-6_14
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