Filaments of crime: Informing policing via thresholded ridge estimation

نویسندگان

چکیده

Objectives: We introduce a new method for reducing crime in hot spots and across cities through ridge estimation. In doing so, our goal is to explore the application of density ridges patrol optimization, contribute policing literature police patrolling reduction strategies. Methods: make use subspace-constrained mean shift algorithm, recently introduced approach estimation further developed cosmology, which we modify extend geospatial datasets spot analysis. Our experiments extract Part I incidents from City Chicago during year 2018 early 2019 demonstrate current data. Results: results nonlinear mode-following agreement with broader kernel estimates. Using predictive extracted data, create multi-run confidence intervals show that templates cover around 94% 0.1-mile envelopes ridges, quickly rising near-complete coverage. also develop provide researchers, as well practitioners, user-friendly open-source software fast Conclusions: following report densities can be used enhance capabilities. empirical tests stability based on past offering an accessible way identifying routes within instead epicenters. suggest research into efficacy patrolling.

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ژورنال

عنوان ژورنال: Decision Support Systems

سال: 2021

ISSN: ['1873-5797', '0167-9236']

DOI: https://doi.org/10.1016/j.dss.2021.113518