Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization
文献类型：期刊论文
| 作者 | Song, Ci1,2; Pei, Tao1,2,3; Ma, Ting1; Du, Yunyan1; Shu, Hua1; Guo, Sihui1; Fan, Zide1 |
| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 2019 |
| 卷号 | 33期号:1页码:134-154 |
| 关键词 | Origin-destination flow spatial local statistics spatial scan statistics ant colony optimization |
| ISSN号 | 1365-8816 |
| DOI | 10.1080/13658816.2018.1516287 |
| 通讯作者 | Pei, Tao(peit@lreis.ac.cn) |
| 英文摘要 | 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. |
| WOS关键词 | NETWORK AUTOCORRELATION ; PATTERNS ; MOBILITY |
| 资助项目 | National Natural Science Foundation of China[41421001] ; National Natural Science Foundation of China[41525004] ; National Natural Science Foundation of China[41601430] ; Key Research Program of Frontier Science, Chinese Academy of Sciences[QYZDY-SSW-DQC007] |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000452083200006 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National Natural Science Foundation of China ; Key Research Program of Frontier Science, Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/51359]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Pei, Tao |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Song, Ci,Pei, Tao,Ma, Ting,et al. Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2019,33(1):134-154. |
| APA | Song, Ci.,Pei, Tao.,Ma, Ting.,Du, Yunyan.,Shu, Hua.,...&Fan, Zide.(2019).Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,33(1),134-154. |
| MLA | Song, Ci,et al."Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 33.1(2019):134-154. |
入库方式： OAI收割
来源：地理科学与资源研究所
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