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Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization
Song, Ci1,2; Pei, Tao1,2,3; Ma, Ting1; Du, Yunyan1; Shu, Hua1; Guo, Sihui1; Fan, Zide1
2019
Source PublicationINTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
ISSN1365-8816
Volume33Issue:1Pages:134-154
Corresponding AuthorPei, Tao(peit@lreis.ac.cn)
AbstractAn 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.
KeywordOrigin-destination flow spatial local statistics spatial scan statistics ant colony optimization
DOI10.1080/13658816.2018.1516287
WOS KeywordNETWORK AUTOCORRELATION ; PATTERNS ; MOBILITY
Indexed BySCI
Language英语
Funding ProjectNational 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]
Funding OrganizationNational Natural Science Foundation of China ; Key Research Program of Frontier Science, Chinese Academy of Sciences
WOS Research AreaComputer Science ; Geography ; Physical Geography ; Information Science & Library Science
WOS SubjectComputer Science, Information Systems ; Geography ; Geography, Physical ; Information Science & Library Science
WOS IDWOS:000452083200006
PublisherTAYLOR & FRANCIS LTD
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Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/51360
Collection中国科学院地理科学与资源研究所
Corresponding AuthorPei, Tao
Affiliation1.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
Recommended Citation
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.
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