Regional Division of police patrols Based on Adaptive FCM Clustering and MMAS

Abstract

Through researching and analyzing adaptive strategy and fuzzy C-means (FCM) clustering algorithm, we put them together to form a n adaptive FCM clustering algorithm. It is a good solution to the problem of local optimum as well as sensitivity to the initial value for the traditional FCM clustering algorithm. Finally, the new algorithm has been used in the divided region of police patrols in a city. In the division of the region, it has been proved by experiments that the sum of distance between a police vehicle and each possible accident scene can achieve the minimum value, which shows a significant effect of police patrols. And through the improved dijkstra algorithm to calculate shortest path length between a police vehicle and an accident scene, it proves that a police vehicle in the division of the region arrives at an accident scene within three minutes after accepting the warnings, whose proportion is 90.2%. On the base of the divided region, we put parameter adaptive thinking and MMAS together to form adaptive MMAS, which is used to calculate optimal patrol circuit in the divi ded region. It proves in the experiment that algorithm efficiency in adaptive ma x-min ant system increases by 2 6.34 % more than non-adaptive max-min ant system under the same condition and has a good prospect for the optimal circuit of police patrols .