Mathematical home burglary model with stochastic long crime trips and patrolling: Applied to Mexico City
作者：
Highlights：
• In this article we propose a stochastic extension of the Jones et al. model for the spatial distribution of home burglary.
• The stochastic model includes the fact that a proportion of burglars is willing to make long trips to burgle faraway homes.
• Trips to distant targets are modeled by long-range jumps following a random motion, which is biased by the attractiveness field.
• The stochastic model allows the formation of central hotspots, these kinds of hotspots are seen in burglary data in urban zones.
• Our Stochastic with long-range jumps model are applied to three different scenarios in Mexico City.
摘要
•In this article we propose a stochastic extension of the Jones et al. model for the spatial distribution of home burglary.•The stochastic model includes the fact that a proportion of burglars is willing to make long trips to burgle faraway homes.•Trips to distant targets are modeled by long-range jumps following a random motion, which is biased by the attractiveness field.•The stochastic model allows the formation of central hotspots, these kinds of hotspots are seen in burglary data in urban zones.•Our Stochastic with long-range jumps model are applied to three different scenarios in Mexico City.
论文关键词：Home burglary,Hotspots,Central hotspots,Attractiveness,Criminal motion,Long-range stochastic jumps
论文评审过程：Received 31 July 2020, Revised 20 October 2020, Accepted 30 November 2020, Available online 23 December 2020, Version of Record 23 December 2020.
论文官网地址：https://doi.org/10.1016/j.amc.2020.125865
