K-means clustering algorithm based on improved Cuckoo search algorithm and its application

Because the K-Means algorithm is easy to fall into the local optimum and the Cuckoo search (CS) algorithm is affected by the step size, this paper proposes a K-Means clustering algorithm based on improved cuckoo search (ICS-Kmeans). The algorithm is compared with the original K-means, the Kmeans alg...

Full description

Saved in:
Bibliographic Details
Published in:2018 IEEE 3rd International Conference on Big Data Analysis (ICBDA) pp. 422 - 426
Main Authors: Ye, Shuce, Huang, Xiaoli, Teng, Yinyin, Li, Yuxia
Format: Conference Proceeding
Language:English
Published: IEEE 01.03.2018
Subjects:
Birds
Classification algorithms
Clustering algorithms
Convergence
cuckoo search
heart sound characteristics
Integrated circuits
K-Means
Optimization
Partitioning algorithms
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract Because the K-Means algorithm is easy to fall into the local optimum and the Cuckoo search (CS) algorithm is affected by the step size, this paper proposes a K-Means clustering algorithm based on improved cuckoo search (ICS-Kmeans). The algorithm is compared with the original K-means, the Kmeans algorithm based on particle swarm optimization (PSO-Kmeans) and the K-Means algorithm based on the cuckoo search (CS-Kmeans). The experimental results show that the proposed algorithm can obtain better clustering effect, faster convergence rate and better accuracy rate through the experimental test on the UCI standard data set. The algorithm is also applied to the clustering of the characteristic parameters of the heart sound MFCC. The results show that a better clustering center can be obtained, the algorithm converges fast.
AbstractList Because the K-Means algorithm is easy to fall into the local optimum and the Cuckoo search (CS) algorithm is affected by the step size, this paper proposes a K-Means clustering algorithm based on improved cuckoo search (ICS-Kmeans). The algorithm is compared with the original K-means, the Kmeans algorithm based on particle swarm optimization (PSO-Kmeans) and the K-Means algorithm based on the cuckoo search (CS-Kmeans). The experimental results show that the proposed algorithm can obtain better clustering effect, faster convergence rate and better accuracy rate through the experimental test on the UCI standard data set. The algorithm is also applied to the clustering of the characteristic parameters of the heart sound MFCC. The results show that a better clustering center can be obtained, the algorithm converges fast.
Author Huang, Xiaoli
Ye, Shuce
Li, Yuxia
Teng, Yinyin
Author_xml – sequence: 1
  givenname: Shuce
  surname: Ye
  fullname: Ye, Shuce
  organization: School of electrical engineering and electronic information, Xihua University
– sequence: 2
  givenname: Xiaoli
  surname: Huang
  fullname: Huang, Xiaoli
  organization: School of electrical engineering and electronic information, Xihua University
– sequence: 3
  givenname: Yinyin
  surname: Teng
  fullname: Teng, Yinyin
  organization: School of electrical engineering and electronic information, Xihua University
– sequence: 4
  givenname: Yuxia
  surname: Li
  fullname: Li, Yuxia
  organization: School of electrical engineering and electronic information, Xihua University
BookMark eNpNj71OwzAURo0EAy28ACx-gQTbN3acsYS_ikosHRBLdePYrUViR3aKxNuDRAem7wxHR_oW5DzEYAm54azknDV36_b-YVUKxnWpQdW1YGdkwSVoVdVN9X5JPl6L0WLI1AzHPNvkw57isI_Jz4eRdphtT2OgfpxS_Prl9mg-Y6TZYjKHfyaGnvo5U5ymwRucfQxX5MLhkO31aZdk-_S4bV-Kzdvzul1tCt-wuZC146CAIygEiVJyq3lfaeWAK9lBZwGEccIKBaaBTnEjuqavHQPUAhwsye1f1ltrd1PyI6bv3ekt_ABarU9-
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/ICBDA.2018.8367720
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 Xplore Digital Library (LUT)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 153864794X
1538647923
9781538647929
9781538647943
EndPage 426
ExternalDocumentID 8367720
Genre orig-research
GroupedDBID 6IE
6IL
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i90t-57f13631a36a35a551e81d486f3165b3be332cf2e263c93b61c2b9d7f03a823f3
IEDL.DBID RIE
IngestDate Thu Jun 29 18:39:40 EDT 2023
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i90t-57f13631a36a35a551e81d486f3165b3be332cf2e263c93b61c2b9d7f03a823f3
PageCount 5
ParticipantIDs ieee_primary_8367720
PublicationCentury 2000
PublicationDate 2018-March
PublicationDateYYYYMMDD 2018-03-01
PublicationDate_xml – month: 03
  year: 2018
  text: 2018-March
PublicationDecade 2010
PublicationTitle 2018 IEEE 3rd International Conference on Big Data Analysis (ICBDA)
PublicationTitleAbbrev ICBDA
PublicationYear 2018
Publisher IEEE
Publisher_xml – name: IEEE
Score 1.7173947
Snippet Because the K-Means algorithm is easy to fall into the local optimum and the Cuckoo search (CS) algorithm is affected by the step size, this paper proposes a...
SourceID ieee
SourceType Publisher
StartPage 422
SubjectTerms Birds
Classification algorithms
Clustering algorithms
Convergence
cuckoo search
heart sound characteristics
Integrated circuits
K-Means
Optimization
Partitioning algorithms
Title K-means clustering algorithm based on improved Cuckoo search algorithm and its application
URI https://ieeexplore.ieee.org/document/8367720
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFA9zePCksonf5ODRbmlem7RHnQ5FGTsMGV5Gkr5qcWtla_37Tdo5Fbx4C8mDwHsPfu_7EXIB3Do-2ude4DQ48LnyYvBDD1HyKNEJBnUw5-lRjkbRdBqPW-Ry0wuDiHXxGfbcsc7lJ4WpXKisH4GwxqB10LekFE2v1lcfDIv794PrmytXrBX11oS_NqbUgDHc_d9Xe6T73XlHxxtM2SctzDvk-cFboIUUauaVm2tgX6iavxTWr39dUIdDCS1ymtXxAXseVOatKGijxD8oVZ7QrFzRH0nrLpkMbyeDO2-9E8HLYlZ6oUx9EOArEApCZc0dtAZnEIkUfBFq0AjATcqRCzAxaOEbruNEpgxUxCGFA9LOixwPCQ2QKTechaXGCiTQKtLW9wHGU2mAMXVEOo4ts_dm6sVszZHjv69PyI7jfFOddUra5bLCM7JtPspstTyvRfUJJ9uXBg
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA6lCnpSacW3OXh022xmn0etlpbW0kOR4qUk2VldbHel3fX3m-zWWsGLt5AMBGYGZr55EnIDXAMfaXPLMRrs2FxYIdiuhejzIJIROmUw53noj0bBdBqOa-R20wuDiGXxGbbMsczlR5kqTKisHYCnnUEN0HdcR-OeqlvruxOGhe1-5_7hzpRrBa016a-dKaXJ6B7877ND0vzpvaPjjVU5IjVMG-RlYC1QGxWq5oWZbKBfqJi_ZhrZvy2osUQRzVKalBECfe4U6j3LaKXGW5QijWiSr-hW2rpJJt3HSadnrbciWEnIcsv1Yxs8sAV4AlyhHR7ULqcTeDHYnitBIgBXMUfugQpBerbiMoz8mIEIOMRwTOppluIJoQ4yYcazsFhpkThSBFKjH2A89hUwJk5Jw7Bl9lHNvZitOXL29_U12etNnoazYX80OCf7RgpVrdYFqefLAi_JrvrMk9XyqhTbFzBgmk0
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=2018+IEEE+3rd+International+Conference+on+Big+Data+Analysis+%28ICBDA%29&rft.atitle=K-means+clustering+algorithm+based+on+improved+Cuckoo+search+algorithm+and+its+application&rft.au=Ye%2C+Shuce&rft.au=Huang%2C+Xiaoli&rft.au=Teng%2C+Yinyin&rft.au=Li%2C+Yuxia&rft.date=2018-03-01&rft.pub=IEEE&rft.spage=422&rft.epage=426&rft_id=info:doi/10.1109%2FICBDA.2018.8367720&rft.externalDocID=8367720