Geographic Profiling from Kinetic Models of Criminal Behavior

نویسندگان

  • George O. Mohler
  • Martin B. Short
چکیده

We consider the problem of estimating the probability density of the “anchor point” (residence, place of work, etc.) of a criminal offender given a set of observed spatial locations of crimes committed by the offender. Starting from kinetic models of criminal motion and target selection, we derive the probability density of anchor points using the Fokker-Planck equation and Bayes’ Theorem. Here, geographic inhomogeneities such as housing densities and geographic barriers (bodies of water, parks, etc.) are naturally incorporated into the probability density estimate, as well as directional bias and distance to crime preferences in offender target selection. The resulting equations are steady state advection-diffusion-reaction PDEs. We test our methodology against crime data provided by the Los Angeles Police Department and our results highlight the benefits of incorporating these elements of criminal behavior and geographic inhomogeneities into profiling estimates.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Geographic Profiling of Criminal Groups for Military Cordon and Search

In the course of counter-insurgency campaigns, military forces expend considerable resources and time conducting cordon and search operations in an effort to interdict and suppress criminal groups. However, these operations have a low success rate, with most operations yielding little intelligence or marginal tactical gains while simultaneously angering the local populace. This paper demonstrat...

متن کامل

Dynamic Analysis for Geographical Profiling of Serial Cases Based on Bayesian-Time Series

The analysis of spatial information has long been considered valuable for police agency within the criminal investigative process. This is especially true for serial crime cases where criminologists and psychologist apply geographical profiling to model criminal mobility distribution and behavior patterns in order to estimate a criminal’s likely residence. In recent years the availability of ad...

متن کامل

Multivariate Chemometrics with Regression and Classification Analyses in Heroin Profiling Based on the Chromatographic Data.

The purpose of this work is to promote and facilitate forensic profiling and chemical analysis of illicit drug samples in order to determine their origin, methods of production and transfer through the country. The article is based on the gas chromatography analysis of heroin samples seized from three different locations in Serbia. Chemometric approach with appropriate statistical tools (multip...

متن کامل

Multivariate Chemometrics with Regression and Classification Analyses in Heroin Profiling Based on the Chromatographic Data.

The purpose of this work is to promote and facilitate forensic profiling and chemical analysis of illicit drug samples in order to determine their origin, methods of production and transfer through the country. The article is based on the gas chromatography analysis of heroin samples seized from three different locations in Serbia. Chemometric approach with appropriate statistical tools (multip...

متن کامل

Framework for Validating Geographic Profiling Using Samples of Solved Serial Crimes

This short paper was prepared for the NIJ Roundtable for Developing an Evaluation Methodology for Geographic Profiling Software (August 10 and 11, 2004) on approaches for validating geographic profiling (GP) methods. The paper presents a framework for validating any GP method or software package using solved serial crimes including data on crime locations and criminal residences or other anchor...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • SIAM Journal of Applied Mathematics

دوره 72  شماره 

صفحات  -

تاریخ انتشار 2012