犯罪时空预测方法研究综述与展望

犯罪时空预测作为预测警务的核心支撑技术,自2000年左右至今得到了快速的发展.本文介绍了犯罪时空预测的实践背景和理论基础,将犯罪时空预测解构为利用历史案件的时空位置、时空环境和个体行为等要素,结合相应的算法模型预测未来案件时空分布的过程.然后,从输入要素的视角对当前的犯罪时空预测方法进行了总结和归纳,将其划分为基于案件...

Overview and Prospect for Spatial-Temporal Prediction of Crime

As the core technology of predictive policing, Spatial-Temporal(ST) prediction of crime has developed rapidly from around 2000 to the present. We introduce the basic theory of ST prediction of crime at the beginning. We regard the ST prediction method of crime as a process combining corresponding models to predict the ST distribution of crimes in the future and deconstruct it into relationships between three objects:case, ST backcloth, and individual behavior. Then, based on the input factors of prediction models, we sum up three current main methods, including ① the prediction method based on the information of cases’ ST location,② the prediction method based on the backcloth and the information of cases’ ST location, and ③ the prediction method based on individual behavior, the backcloth, and the information of cases’ ST location. We further summarize the mechanisms of different methods in detail respectively. In addition, we compare and analyze each method based on their applicable scenarios and predictive capacities. Finally, with the development of big data technology, we present solutions to improve current prediction methods, that are to construct a data-fusion system, refine data granularity, and integrate new types of data. For model optimization, we need to improve the ability of integrating heterogeneous data from multiple sources and balancing the interpretability and predictive ability of models.