地理科学 ›› 2018, Vol. 38 ›› Issue (8): 1210-1217.doi: 10.13249/j.cnki.sgs.2018.08.002
收稿日期:
2018-01-24
修回日期:
2018-03-02
出版日期:
2018-08-20
发布日期:
2018-08-20
作者简介:
作者简介:方嘉良(1992-),男,广东广州人,硕士研究生,主要从事GIS时空数据挖掘研究。E-mail:
基金资助:
Received:
2018-01-24
Revised:
2018-03-02
Online:
2018-08-20
Published:
2018-08-20
Supported by:
摘要:
针对犯罪地理目标模型(CGT模型)在系列案件嫌疑人落脚点预测中未考虑地理环境因素影响,预测精度不高的问题,提出了一种顾及地理环境因素的犯罪地理目标模型优化方法(GEO-CGT模型)。研究采用相关性分析与灰色关联分析,刻画嫌疑人落脚点的地理环境相关性;参考多分类器系统理论,将地理环境因素与CGT模型进行非线性组合优化,并从搜索距离、面积误差对预测结果进行精度评估。以清远和韶关两市系列财产犯罪案件为样例数据,对模型预测进行对比实验,结果表明,改进后模型的预测精度相比于CGT和GEO-CGT模型均有显著提高。研究拓展了系列案嫌疑人落脚点预测方法,有效地提高了预测精度,对于警方缩小搜索范围,增大成功抓捕犯罪嫌疑人概率具有重要应用意义。
中图分类号:
方嘉良, 李卫红. 系列案犯罪地理目标模型优化[J]. 地理科学, 2018, 38(8): 1210-1217.
Jialiang Fang, Weihong Li. Optimization of Criminal Geographic Targeting Model of Crimes in Series Cases[J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(8): 1210-1217.
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