Volume 6 Number 2 (Feb. 2011)
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JCP 2011 Vol.6(2): 313-320 ISSN: 1796-203X
doi: 10.4304/jcp.6.2.313-320

Regional Division of Police Patrols Based on Adaptive FCM Clustering and MMAS

Shengdong Li1, Xueqiang Lv1, 2, Chenglin Zhan3, and Shuicai Shi1, 2
1Chinese Information Processing Research Center, Beijing Information Science and Technology University, Beijing, China
2Beijing TRS Information Technology Co., Ltd., Beijing, China
3Collaborative Support Technology Lab, Jilin University, Changchun, China


Abstract—Through researching and analyzing adaptive strategy and fuzzy C-means (FCM) clustering algorithm, we put them together to form an 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 divided region. It proves in the experiment that algorithm efficiency in adaptive max-min ant system increases by 26.34% more than non-adaptive max-min ant system under the same condition and has a good prospect for the optimal circuit of police patrols.

Index Terms—fcm, adaptive, mmas, regional division

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Cite: Shengdong Li, Xueqiang Lv, Chenglin Zhan, and Shuicai Shi, "Regional Division of Police Patrols Based on Adaptive FCM Clustering and MMAS," Journal of Computers vol. 6, no. 2, pp. 313-320, 2011.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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