基于布谷鸟算法的游行运动趋势仿真研究

J4 ›› 2014, Vol. 36 ›› Issue (10): 1979-1984.

基于布谷鸟算法的游行运动趋势仿真研究

巩青歌1，王丹青2

（1.武警工程大学科研部研究所,陕西西安 710086;2.武警工程大学研究生管理大队,陕西西安 710086）

收稿日期:2014-06-05 修回日期:2014-08-21 出版日期:2014-10-25 发布日期:2014-10-25

Simulation research on the parade trend prediction
based on the cuckoo search algorithm

GONG Qingge1,WANG Danqing2

(1.Institute of Scientific Research,Engineering University of the Chinese Armed Police Force,Xi’an 710086;
2.Management Team of Postgraduate,Engineering University of the Chinese Armed Police Force,Xi’an 710086,China)

Received:2014-06-05 Revised:2014-08-21 Online:2014-10-25 Published:2014-10-25

摘要/Abstract

摘要：

近年来，我国进入深化改革社会转型关键期，特殊的历史时期使得社会呈现出群体性事件发生愈加频繁，这类事件处理稍有不慎，事态升级迅速，后果不堪设想。通过分析社会学、心理学对游行事件研究的理论成果，提出了面向游行运动建模需要的城市交通路网的简化模型，并在此基础之上利用寻优能力较为突出的布谷鸟算法对游行人流运动趋势进行预测，通过AnyLogic仿真软件对算法进行了仿真实验，验证了这一预测方法的合理性，表明其中的关键算法具有较高的适用性，可以为研究游行事件发展的一般规律以及在处置中预先抢占先机提供有力的技术支撑。

关键词: 游行事件, 布谷鸟算法, 趋势, AnyLogic仿真

Abstract:

Recently,our country has stepped into the critical period of social transformation,which makes the society a special historical period of frequent occurrence of mass incidents. If they are not taken properly,the situation will rapidly expand.Through analyzing the theoretical study results of sociology and psychology on parade,a movement model based on a simplified urban traffic network is proposed, and the Cuckoo Search (CS) algorithm is adopted to predict parade flow trends.The simulation results using AnyLogic simulation software verify the rationality of the model and the effectiveness of the key algorithm, which also provides some general rules of parade event development and technological support for handling such events.

Key words: parade;Cuckoo search algorithm;trend;AnyLogic simulation

巩青歌1，王丹青2. 基于布谷鸟算法的游行运动趋势仿真研究[J]. J4, 2014, 36(10): 1979-1984.

GONG Qingge1,WANG Danqing2. Simulation research on the parade trend prediction
based on the cuckoo search algorithm [J]. J4, 2014, 36(10): 1979-1984.

参考文献［10］

［1］	Ren Hongjie. Frontier exploration of social stability problems ［M］. Beijing:Chinese People’s Public Security University Press,2005.(in Chinese)
［2］	Shi Feng,Wang Hui,Yu Lei,et al. 30 Matlab intelligent algorithms［M］.Beijing:Beihang University Press,2010.(in Chinese)
［3］	Xiang Youjun,Wu Zongze,Xie Shengli. Fast motion estimation algorithm based on moving direction prediction［J］. Computer Engineering,2009,24(35):2022. (in Chinese)
［4］	Research Group of Chinese Administrative Management Society. China sudden mass incidents［M］.Beijing:National School of Administration Press,2009. (in Chinese)
［5］	Yu Jianrong. The main types of the current group incidents in China and its characteristics［J］. Journal of China University of Political Science and Law,2009,7(6):3439. (in Chinese)
［6］	Li Ying. Preventive mechanism of mass incidents ［J］. Social Science,2006,23(2):1524. (in Chinese)
［7］	Liu Dehai,Wang Weiguo. Evolutionary game analysis of generating mechanism of different social structures of group emergencies［J］. Systems Engineering,2010,13(6):3440. (in Chinese)
［8］	Xiao Tangbiao. Research on group events［M］.Shanghai:Academic Press,2011. (in Chinese)
［9］	Chen Yuanjiang,Duan Li,Xiao Bin.Principal component analysis method and the Delphy building index method of driving behavior ［J］. Journal of Safety and Environment,2012,12(2):228232. (in Chinese)
［10］	Gao Shutao.Short term traffic flow prediction of model based on neural network and Cuckoo search algorithm［J］. Computer Engineering and Applications,2013, 49（9）：106109. (in Chinese)
［11］	Granovetter M．Threshold models of collective behavior［J］．American Journal of Sociology, 1978,83(6):14201443．
［12］	Yang X S，Deb S.Engineering optimization by cuckoo search［J］.International Journal of Mathematical Modeling and Numerical Optimization，2010，11（4）：330343.
	附中文参考文献:
［1］	任红杰.社会稳定问题前沿探索［M］.北京：中国人民公安大学出版社,2005.
［2］	史峰,王辉,郁磊,等.Matlab智能算法30例［M］.北京：北京航空航天大学出版社,2010.
［3］	向友君,吴宗泽,谢胜利.基于运动方向预测的快速运动估计算法［J］.计算机工程,2009,24(35):2022.
［4］	中国行政管理学会课题组.中国群体性突发事件［M］.北京：国家行政学院出版社,2009.
［5］	于建嵘.当前我国群体性事件的主要类型及其基本特征［J］.中国政法大学学报,2009,7(6):3439.
［6］	李莹.试析群体性事件的预防机制［J］.社科纵横,2006,23(2):1524.
［7］	刘德海,王维国.不同社会结构下群体性突发事件产生机理的演化博弈分析［J］.系统工程,2010,13(6):3440.
［8］	肖唐鏢.群体性事件研究［M］.上海：学林出版社,2011.
［9］	陈沅江,段莉,肖赟. 主成分分析法和德尔菲结合法的影响驾驶行为指标构建［J］. 安全与环境学报,2012,12(2):228232.
［10］	高述涛.CS 算法优化 BP神经网络的短时交通流量预测［J］.计算机工程与应用，2013, 49（9）：106109.

[1]	郁伟生1，邓伟1，张瑶2，李蜀瑜1,2. 基于时间序列的音乐流行趋势预测研究[J]. 计算机工程与科学, 2018, 40(09): 1703-1709.
[2]	夏卓群1,2,3,罗君鹏1,2,胡珍珍1,2. 移动感知环境下基于CSA-SSVR的交通状态预测方法[J]. 计算机工程与科学, 2018, 40(08): 1482-1487.
[3]	金培权，郝行军，岳丽华. 面向新型存储的大数据存储架构与核心算法综述[J]. J4, 2013, 35(10): 12-24.