ROCR: visualizing classifier performance in R
Bioinformatics
Detecting space-time anomalies in point process models of intelligent site selection
Detecting space-time anomalies in point process models of intelligent site selection
Decision Support Systems - Special issue: Intelligence and security informatics
A statistical threat assessment
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Previous academic research has identified the correlation between special events and crime rates within cities. However, in much of the previous work, the focus was either on spatial or temporal analysis related to the evolution of local crime patterns in conjunction with the special events. This research uses a hybrid agent-based simulation to examine the impact of temporal pulse events on the criminal site selection process. The simulation provides researchers with a method for adjusting both the temporal and spatial patterns in response to a series of a-priori special events. Using the data from this simulation, we illustrate the effectiveness of a new modeling approach. Initial results show that adding a hierarchical framework to a feature-space regression model improves crime prediction accuracy and offers the law enforcement analyst better insight into both the temporal and spatial considerations of criminals. Improving the ability of law enforcement to identify, and prepare for, spatial-temporal shifts in crime patterns will significantly enhance proactive policing operations and resource allocation planning in support of large special events.