NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM

Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is proved. An empirical study of their convergence behavior is discussed. The performance of the new algorithms is compared with the fuzzy c-means algorithm by testing them on four published data sets. Expe...

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Main Author: Kamel, M.S. (author)
Other Authors: Selim, S.Z. (author), unknown (author)
Format: article
Published: 2020
Subjects:
Online Access:https://eprints.kfupm.edu.sa/id/eprint/2559/1/new_algorithms_for_solving_the_fuzzy_clu_kamel_isi_a1994nk07400008.pdf
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author Kamel, M.S.
author2 Selim, S.Z.
unknown
author2_role author
author
author_facet Kamel, M.S.
Selim, S.Z.
unknown
author_role author
dc.creator.none.fl_str_mv Kamel, M.S.
Selim, S.Z.
unknown
dc.date.*.fl_str_mv 2020
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/2559/1/new_algorithms_for_solving_the_fuzzy_clu_kamel_isi_a1994nk07400008.pdf
NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM. PATTERN RECOGNITION, 27. pp. 421-428.
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv PERGAMON-ELSEVIER SCIENCE LTD
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/2559/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is proved. An empirical study of their convergence behavior is discussed. The performance of the new algorithms is compared with the fuzzy c-means algorithm by testing them on four published data sets. Experimental results show that the new algorithms are faster and lead to computational savings.
eu_rights_str_mv openAccess
format article
id KFUPM_ad3d5935c8bdab920b609a606381f4c9
identifier_str_mv NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM. PATTERN RECOGNITION, 27. pp. 421-428.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::2559
publishDate 2020
publisher.none.fl_str_mv PERGAMON-ELSEVIER SCIENCE LTD
repository.mail.fl_str_mv
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spelling NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEMKamel, M.S.Selim, S.Z.unknownComputerTwo new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is proved. An empirical study of their convergence behavior is discussed. The performance of the new algorithms is compared with the fuzzy c-means algorithm by testing them on four published data sets. Experimental results show that the new algorithms are faster and lead to computational savings.PERGAMON-ELSEVIER SCIENCE LTDArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/2559/1/new_algorithms_for_solving_the_fuzzy_clu_kamel_isi_a1994nk07400008.pdf NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM. PATTERN RECOGNITION, 27. pp. 421-428. enhttps://eprints.kfupm.edu.sa/id/eprint/2559/2020info:eu-repo/semantics/openAccessoai::25592019-11-01T13:44:50Z
spellingShingle NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
Kamel, M.S.
Computer
status_str publishedVersion
title NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
title_full NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
title_fullStr NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
title_full_unstemmed NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
title_short NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
title_sort NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/2559/1/new_algorithms_for_solving_the_fuzzy_clu_kamel_isi_a1994nk07400008.pdf