【摘要】：針對犯罪空間聚集態(tài)研究算法中有關(guān)窗寬優(yōu)化選擇問題,將動態(tài)優(yōu)化窗寬算法與DENCLUE(DENsity-based CLUstEring)算法結(jié)合,提出一種新的聚類算法。以入室盜竊案件為例,研究了該算法在犯罪熱點探測方面的應(yīng)用。結(jié)果顯示引入優(yōu)化窗寬算法后,可得到較為精確的聚類中心位置及概率密度變化趨勢,并且當(dāng)格網(wǎng)邊長與鄰近格網(wǎng)距離閾值及鄰近點距離閾值之比為2:3:1時會得到較好的熱點分析結(jié)果。通過分析犯罪熱點分布圖,可協(xié)助公安機關(guān)調(diào)整警力配置,加強案件高發(fā)區(qū)警力巡邏。
[Abstract]:In order to solve the problem of optimal window width selection in crime spatial aggregation algorithm, a new clustering algorithm is proposed by combining dynamic optimization window width algorithm with DENCLUE (DENsity-based CLUstEring) algorithm. Taking the burglary case as an example, the application of this algorithm in the detection of crime hotspots is studied. The results show that the location of clustering center and the change trend of probability density can be obtained by introducing the optimized window width algorithm. When the ratio of the edge length to the distance threshold of the adjacent grid and the threshold of the distance between the adjacent points is 2:3:1, a better hot spot analysis result can be obtained. By analyzing the distribution map of crime hot spots, we can assist the public security organs to adjust the police force allocation and strengthen the police patrol in the areas with high incidence of cases.
【作者單位】： 清華大學(xué)工程物理系公共安全研究中心;
【基金】：國家自然科學(xué)基金資助項目(70773069)
【分類號】：D917

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1 顏峻;袁宏永;疏學(xué)明;鐘少波;;用于犯罪空間聚集態(tài)研究的優(yōu)化聚類算法[J];清華大學(xué)學(xué)報(自然科學(xué)版)網(wǎng)絡(luò).預(yù)覽;2009年02期

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本文編號：2288140