Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization
Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization
复制标题
使用蚁群优化检测起点-目的地流中的任意形状的集群
DOI：
10.1080/13658816.2018.1516287
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发表时间：
2018-09
影响因子：
5.7
通讯作者：
Fan Zide
中科院分区：
文献类型：
--
作者：
Song Ci;Pei Tao;Ma Ting;Du Yunyan;Shu Hua;Guo Sihui;Fan Zide
原点-目的地流可以定义为物体在两个位置之间的运动。这些运动必须出于一系列目的而确定，并且可以通过OD流的聚类直观地表示强烈的相互作用。识别这些集群可能对城市规划、交通规划和物流管理研究有用。然而，很少有方法可以识别任意形状的流簇。本文提出了一种基于蚁群优化（ACO）的空间扫描统计方法，用于检测任意形状的OD流簇（AntScan_flow）。本研究将OD流聚类定义为具有显著对数似然比（LLR）的区域对，并利用蚁群算法在搜索空间中检测具有显著对数似然比最大的聚类。基于AntScan_flow和SaTScan_flow的仿真实验表明，基于准确率，AntScan_flow具有更好的性能，但计算量较大。最后，以北京市居民早晨通勤流为例进行了实证研究。AntScan_flow结果表明，中远通勤OD流集聚区与城市地铁、高速公路高度一致。此外，短途通勤OD流集聚区更有可能呈现“居住区-工作区”模式。
ABSTRACT An origin-destination (OD) flow can be defined as the movement of objects between two locations. These movements must be determined for a range of purposes, and strong interactions can be visually represented via clustering of OD flows. Identification of such clusters may be useful in urban planning, traffic planning and logistics management research. However, few methods can identify arbitrarily shaped flow clusters. Here, we present a spatial scan statistical approach based on ant colony optimization (ACO) for detecting arbitrarily shaped clusters of OD flows (AntScan_flow). In this study, an OD flow cluster is defined as a regional pair with significant log likelihood ratio (LLR), and the ACO is employed to detect the clusters with maximum LLRs in the search space. Simulation experiments based on AntScan_flow and SaTScan_flow show that AntScan_flow yields better performance based on accuracy but requires a large computational demand. Finally, a case study of the morning commuting flows of Beijing residents was conducted. The AntScan_flow results show that the regions associated with moderate- and long-distance commuting OD flow clusters are highly consistent with subway lines and highways in the city. Additionally, the regions of short-distance commuting OD flow clusters are more likely to exhibit ‘residential-area to work-area’ patterns.
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影响因子：
2.9
作者：
Gil NS;Han JY;Ok SH;Shin IW;Lee HK;Chung YK;Sohn JT
通讯作者：
Sohn JT
DOI：
10.1109/fskd.2015.7381919
发表时间：
2015-08
期刊：
2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)
影响因子：
--
作者：
Nan Ye;Rongwei Zhang;Kena Yu;Dehong Wang
通讯作者：
Nan Ye;Rongwei Zhang;Kena Yu;Dehong Wang
DOI：
10.1007/978-3-642-01020-0_2
发表时间：
2009-04
期刊：
--
影响因子：
--
作者：
T. Stützle
通讯作者：
T. Stützle
影响因子：
3.6
作者：
B. Zhu
通讯作者：
B. Zhu
DOI：
10.1007/978-1-4899-7687-1_22
发表时间：
2017
期刊：
--
影响因子：
--
作者：
Marco Dorigo;M. Birattari
通讯作者：
Marco Dorigo;M. Birattari