论文标题
部分可观测时空混沌系统的无模型预测
Understanding the illicit drug distribution in England: a data-centric approach to the County Lines Model
论文作者
论文摘要
县线模型（CLM）是在英国发现的一种相对较新的非法药物分配方法。 CLM带来了现代的奴隶制和公共卫生问题，同时需要挑战执法能力，因为必须在不同的地方警察之间进行协调。我们的目标是在两个地方之间建立连接时，了解线路运营商背后的领土逻辑。我们使用三种不同的空间模型（重力，辐射和零售模型），因为他们每个人都以不同的方式了解从位置I到J的流动。使用伦敦大都会警察的公共数据，我们训练和跨估算模型，以了解建立联系时考虑哪些不同的物理和社会人口统计学变量。我们还通过毒品，可支配的家庭收入，警察在场和刀具犯罪事件以及特定地点的人口以及两个不同之间的距离和旅行时间来分析住院。我们的结果表明，刀具犯罪事件和滥用毒品的住院是最重要的变量。我们还发现，伦敦运营商分发给了英格兰“南部”的领土，因为在它之外观察到了它们的存在。
The County Lines Model (CLM) is a relatively new illicit drugs distribution method found in Great Britain. The CLM has brought modern slavery and public health issues, while challenging the law-enforcement capacity to act, as coordination between different local police forces is necessary. Our objective is to understand the territorial logic behind the line operators when establishing a connection between two places. We use three different spatial models (gravity, radiation and retail models), as each one of them understands flow from place i to j in a different way. Using public data from the Metropolitan Police of London, we train and cross-validate the models to understand which of the different physical and socio-demographic variables are considered when establishing a connection. We analyse hospital admissions by drugs, disposable household income, police presence and knife crime events, in addition to the population of a particular place and the distance and travel times between two different. Our results show that knife crime events and hospital admissions by misuse of drugs are the most important variables. We also find that London operators distribute to the territory known as the "South" of England, as negligible presence of them is observed outside of it.
