Mathematical modeling approach to crime and prediction of criminological patterns

 This research examine advanced applications of mathematical methods in criminology and sheds light on their role in analyzing and modeling complex social phenomena such as crime. The main goal is to analyze the capabilities of mathematical models in identifying crime patterns, predicting future trends, and evaluating the effectiveness of preventive strategies.

The research was conducted in a theoretical and descriptive-analytical manner, using a literature review and analysis of mathematical models. Mathematical approaches including dynamical systems, network analysis, and game theory were examined, and empirical data were used to adapt these models.

The findings show that mathematical models are able to identify spatiotemporal patterns of crime, such as hot spots and revictimization, and predict future trends. They also provide tools for simulating criminal behavior and evaluating the effects of preventive policies. The potential of these methods in designing crime reduction strategies and developing operational tools is emphasized.