多要素约束下的非法游行路径动态预测方法

A multi-factor constrained dynamic prediction method of illegal parade paths

非法游行事件严重危害社会秩序,非法游行群体移动路径的精准预测对区域警力的高效布控具有重要指导作用。现有相关研究无法同时顾及游行事件中吸引要素和排斥要素对游行群体路径选择的综合影响,导致对游行群体未来移动路径的预测精度低。为此,提出了一种多要素约束下的非法游行路径动态预测方法。首先借助距离衰减理论,耦合游行群体实时位置和地理多要素空间分布构建动态加权无向图,在此基础上建立多要素约束的路径优化数学模型,利用Floyd算法求解游行群体当前位置与目的地间的移动路径。通过对3个非法游行历史事件进行实验对比分析发现,所提方法预测结果与真实游行路径在长度、路段和节点3个维度的吻合度均高于80%,比现有方法更精准有效。

Illegal parade incidents seriously harm the public order.The accurate prediction of illegal parade paths will be guidable for the efficient deployment of police force.Existing related studies mostly do not consider the comprehensive influence of the attraction factors and the repulsion factors on path selection of parade groups,resulting in the low precision of the prediction of the parade movement path.Therefore,this paper proposes a multi-factor constrained dynamic prediction method of illegal parade paths.Specifically,a dynamic weighted undirected graph is firstly constructed by combining the real-time locations of the parade group with the spatial distributions of multiple factors based on the distance decay theory.Then,an optimization model is built with the constraints of multiple factors,and the Floyd algorithm is employed to predict the parade paths from the parade group’s current position to the destination.Comparative experiments on three historical illegal parades show that the matching degrees between the obtained results by the proposed method and the real parade paths are higher than 80%in terms of path length,road segments and road network nodes,demonstrating the efficiency and advan-tages of the proposed method.