Spatial clustering algorithm with obstacles constraints by quantum particle swarm optimization and K-Medoids

The classical K-Medoids algorithm is easily trapped into local extremum and is sensitive to initialization. After analyzed the existing algorithms of spatial clustering with obstacles constraints, the paper proposed a new spatial clustering algorithm with obstacles constraints combined QPSO with K-M...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2010 Second International Conference on Computational Intelligence and Natural Computing Jg. 2; S. 105 - 108
Hauptverfasser: Yang Teng-Fei, Zhang Xue-Ping
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.09.2010
Schlagworte:
Algorithm design and analysis
Clustering algorithms
Convergence
K-Medoids algorithm
obstacle constraints
Optimization
Particle swarm optimization
Partitioning algorithms
QPSO algorithm
spatial clustering
Sun
ISBN:9781424477050, 1424477050
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract The classical K-Medoids algorithm is easily trapped into local extremum and is sensitive to initialization. After analyzed the existing algorithms of spatial clustering with obstacles constraints, the paper proposed a new spatial clustering algorithm with obstacles constraints combined QPSO with K-Medoids, which named QKSCO. This algorithm introduced QPSO's rapid global convergence to separating the global clusters firstly, then it finds the optimal exact solutions of clusters by K-Medoids; and it called the two algorithms to improving the efficiency of the implementation of the new algorithm coordinating. The experimental results indicated that the algorithm has better time complexity and clustering efficiency.
AbstractList The classical K-Medoids algorithm is easily trapped into local extremum and is sensitive to initialization. After analyzed the existing algorithms of spatial clustering with obstacles constraints, the paper proposed a new spatial clustering algorithm with obstacles constraints combined QPSO with K-Medoids, which named QKSCO. This algorithm introduced QPSO's rapid global convergence to separating the global clusters firstly, then it finds the optimal exact solutions of clusters by K-Medoids; and it called the two algorithms to improving the efficiency of the implementation of the new algorithm coordinating. The experimental results indicated that the algorithm has better time complexity and clustering efficiency.
Author Yang Teng-Fei
Zhang Xue-Ping
Author_xml – sequence: 1
  surname: Yang Teng-Fei
  fullname: Yang Teng-Fei
  organization: Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
– sequence: 2
  surname: Zhang Xue-Ping
  fullname: Zhang Xue-Ping
  organization: Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
BookMark eNpVUM1OwzAYCwIkYOwBEJe8QEf-2ixHVPEzMeDA7lPSfhlBbVKSVNN4eiqxCz7Ysmz54Ct05oMHhG4oWVBK1F29eqsXjEy2rASXsjpBcyWXVDAhpCSVPP3nS3KB5il9kQklk4JUl6j7GHR2usNNN6YM0fkd1t0uRJc_e7yfGAeTsm46SLgJPuWonc8JmwP-HrXPY48HHbObCjjtdexxGLLr3c80GzzWvsUvxSu0wbXpGp1b3SWYH3WGNo8Pm_q5WL8_rer7deEUyUUJjGtleVtaC0RZbSywZSMqRlsLZgpL4EYo0lhDgYuWLpW0pmGqYpJpyWfo9m_WAcB2iK7X8bA9XsR_ATnYXxo
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/CINC.2010.5643776
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9781424477067
9781424477043
1424477069
1424477042
EndPage 108
ExternalDocumentID 5643776
Genre orig-research
GroupedDBID 6IE
6IF
6IK
6IL
6IN
AAJGR
AAWTH
ADFMO
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
IEGSK
IERZE
OCL
RIE
RIL
ID FETCH-LOGICAL-i90t-5e23a9f3d5ffe09fabfe28c4621dfeb23a5e3b490cfb1e34d1897fbc296272a73
IEDL.DBID RIE
ISBN 9781424477050
1424477050
IngestDate Wed Aug 27 02:52:40 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i90t-5e23a9f3d5ffe09fabfe28c4621dfeb23a5e3b490cfb1e34d1897fbc296272a73
PageCount 4
ParticipantIDs ieee_primary_5643776
PublicationCentury 2000
PublicationDate 2010-Sept.
PublicationDateYYYYMMDD 2010-09-01
PublicationDate_xml – month: 09
  year: 2010
  text: 2010-Sept.
PublicationDecade 2010
PublicationTitle 2010 Second International Conference on Computational Intelligence and Natural Computing
PublicationTitleAbbrev CINC
PublicationYear 2010
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0000527406
Score 1.4535669
Snippet The classical K-Medoids algorithm is easily trapped into local extremum and is sensitive to initialization. After analyzed the existing algorithms of spatial...
SourceID ieee
SourceType Publisher
StartPage 105
SubjectTerms Algorithm design and analysis
Clustering algorithms
Convergence
K-Medoids algorithm
obstacle constraints
Optimization
Particle swarm optimization
Partitioning algorithms
QPSO algorithm
spatial clustering
Sun
Title Spatial clustering algorithm with obstacles constraints by quantum particle swarm optimization and K-Medoids
URI https://ieeexplore.ieee.org/document/5643776
Volume 2
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFA_b8OBJZRO_ycGjcWnTpM15OAR17DBkt5GmiQ7WdfZD8b_3pa0VwYuX0g8I5eXx8r5-74fQdehrX1iPERnElICGCBJpQYlmXiKE0ZzV-Irnx3A2i5ZLOe-hmw4LY4ypm8_Mrbuta_lJpiuXKhtzV2UKRR_14dpgtbp8CuUQX1Hxjd0KQ8q7kU7fz21V06NyPIGYuWnsahf9xa5SHy7Tg__91iEa_aD08Lw7f45Qz2yHaOM4hkGnsN5UbgYCfMFq85Ll6_I1xS7rirMYPELXDIe1cw4dR0RZ4PgTv1Ug5irFu1adcPGh8hRnYFXSFq6J1TbBD-TJgClMihFaTO8Wk3vSMiqQtaQl4cZnSlqWcGsNlVbF1viRDoTvJRZCbKa4YXEgqbaxZ1iQeJEMbax9x9Djq5Ado8E225oThAPwNAz4Ch7sdKA1mG8IjViklLY8gYVP0dAJarVrZmasWhmd_f36HO03VXnXu3WBBmVemUu0p9_LdZFf1Rv9BbcdqQU
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1bS8MwFA5zCvqksol38-CjdWnTpM3zcEx2YQ9D9jbSXHSwtbMXxX9v0nYVwRff2gZCOTmcnNt3PgDuA094VLvYYX6EHKMh1AkFRY7ArqRUCYJLfMXLOJhOw8WCzVrgocHCKKXK5jP1aB_LWr5MRGFTZT1iq0wB3QP7ljmLVGitJqOCiImwEN2ht4IAkWao0-69rmu6iPX6JmquWrvqbX_xq5TXy-D4fz92Aro_OD04a26gU9BScQesLcuw0Soo1oWdgmBWIF-_Jukqf9tAm3eFSWR8QtsOB4V1Dy1LRJ7B6Au-F0bQxQZua4WC2SdPNzAxdmVTAzYhjyUcORNljKHMumA-eJr3h07NqeCsGModojzMmcaSaK0Q0zzSyguFTz1XahNkY04UjnyGhI5chX3phizQkfAsR4_HA3wG2nESq3MAfeNrKOMtuOasfSGMATfBEQ45F5pIs_EF6FhBLbfV1IxlLaPLvz_fgcPhfDJejp-noytwVNXobSfXNWjnaaFuwIH4yFdZelse-je2RKxQ
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2010+Second+International+Conference+on+Computational+Intelligence+and+Natural+Computing&rft.atitle=Spatial+clustering+algorithm+with+obstacles+constraints+by+quantum+particle+swarm+optimization+and+K-Medoids&rft.au=Yang+Teng-Fei&rft.au=Zhang+Xue-Ping&rft.date=2010-09-01&rft.pub=IEEE&rft.isbn=9781424477050&rft.volume=2&rft.spage=105&rft.epage=108&rft_id=info:doi/10.1109%2FCINC.2010.5643776&rft.externalDocID=5643776
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424477050/lc.gif&client=summon&freeimage=true
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424477050/mc.gif&client=summon&freeimage=true
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424477050/sc.gif&client=summon&freeimage=true