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Determining the Geographical Origin of a Serial Offender Considering the Temporal Uncertainty of the Recorded Crime Data

机译:确定串行罪犯的地理来源,考虑到记录犯罪数据的时间不确定性

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Since the days the investigating officers used "pin maps" to locate and to think about crime events, crime mapping has become widespread thanks to spatial analysis mainly supplied by GIS-like software. In particular these methods suit well to geographic profiling devoted to crime series characterised by a single offender and hence limited space and time variability. Although spatial techniques are now regularly performed to delineate an offender's area of residence, the temporal dimension is underemployed due to the wider uncertainty of time records. This paper proposes a methodology based on a least-squares adjustment in order to cope with this temporal issue for determining the most probable offender's residence. Moreover, a chi-square test is described to check the significance of the solutions suggested by the method. The process is carried out on the real road network which has been discretised (rasterised) for computing convenience. Three simulations show the validity of the reasoning. Finally the main time and speed assumptions introduced in the model are discussed paving the way for further research.
机译:自调查人员使用“PIN地图”的日子来定位并思考犯罪事件,由于GIS样软件主要提供的空间分析,犯罪映射已变得普遍。特别是这些方法适合致力于犯罪系列的地理分析,其特征在于单一罪犯,因此有限的空间和时间可变性。虽然现在定期进行空间技术以描绘罪犯的住宅区域,但由于时间记录的不确定性更广泛,延时就业不足。本文提出了一种基于最小二乘调整的方法,以应对这种时间问题,以确定最可能的罪犯的住所。此外,描述了Chi-Square测试来检查该方法所提出的解决方案的重要性。该过程是在真实的道路网络上进行的,该路线被离散(光栅)以便计算方便。三种模拟显示了推理的有效性。最后讨论了模型中引入的主时间和速度假设,讨论了进一步研究的方式铺平道路。

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