预测连环犯罪区域的地理画像法研究

Geographic Profile of Serial Crime Region

为了更快速精准预测犯罪高发区的地理定位,研究一种根据评估连环犯罪者的居住地来预测犯罪高发区的地理画像法.先根据连环犯罪的作案地点,利用简化的CGT模型快速定位罪犯居住地;然后利用最大似然估计的概念及贝叶斯分布分析建立一个考虑地理偏好和人口密集度的多元模型来预测犯罪地点.最后结合真实案例证实了模型的有效性.

In order to quickly predict and spot possible crime scene area, a geographic portrait method which is based on the evaluation of the residential places of a serial criminal was worked out. First, based on the crime scenes of a serial crime, a simplified CGT model is employed to spot the criminal＇s domicile; then by using the concept of the maximum likelihood esti- mate Bayesian distribution, a multiple-dimension model which incorporates geographic bias and population density is construc- ted so as to predict the crime site. Lastly the efficacy of this model is proved via real criminal cases.