Cycle connectivity and cyclic connectivity index of intuitionistic fuzzy graphs1

Cycle connectivity and cyclic connectivity index of intuitionistic fuzzy graphs1

Connectivity parameters play a crucial role in network analysis. The cyclic reachability is an important attribute that determines the connectivity of the network, the strength of the cycles in intuitionistic fuzzy graphs (IFGs) is not unique. This article first introduces several concepts of cycle...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of intelligent & fuzzy systems 2023-04, Vol.44 (4), p.6737-6748
Hauptverfasser: Gong, Zengtai, He, Lele
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 6748
container_issue 4
container_start_page 6737
container_title Journal of intelligent & fuzzy systems
container_volume 44
creator Gong, Zengtai
He, Lele
description Connectivity parameters play a crucial role in network analysis. The cyclic reachability is an important attribute that determines the connectivity of the network, the strength of the cycles in intuitionistic fuzzy graphs (IFGs) is not unique. This article first introduces several concepts of cycle connectivity of IFGs, and then discusses the related properties. On the basis of the cycle connectivity of IFGs, the concepts of cyclic connectivity index ( CCI ) and average cyclic connectivity index ( ACCI ) are proposed, which can be used to express the reachability of cycle. Some results of CCI on IFGs are discussed, such as cutvertices, trees, and complete intuitionistic fuzzy graphs. The vertices of IFGs are divided into three categories according to ACCI . Two algorithms are introduced, one to find CCI and ACCI of a given IFGs and the other to identify the nature of vertices.
doi_str_mv 10.3233/JIFS-222332
format Article
fullrecord <record><control><sourceid>crossref</sourceid><recordid>TN_cdi_crossref_primary_10_3233_JIFS_222332</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_3233_JIFS_222332</sourcerecordid><originalsourceid>FETCH-LOGICAL-c121t-a7aad1f61494a7ff6ca47dacb69c6b15625286c84bc606566c463f5112a018563</originalsourceid><addsrcrecordid>eNpVkE1Lw0AURQdRsFZX_oHsZXTefLxJlhKsVgoK6jpMXjI6UpOSmYrprzelblzdw-VyF4exSxDXSip187hcvHApJ5RHbAa5NTwv0B5PLFBzkBpP2VmMn0KANVLM2HM50rrNqO-6llL4DmnMXNdkNNWB_veha9qfrPcTpG1Ioe9CTNPIb3e7MXsf3OYjwjk78W4d24u_nLO3xd1r-cBXT_fL8nbFCSQk7qxzDXgEXWhnvUdy2jaOaiwIazAojcyRcl0TCjSIpFF5AyCdgNygmrOrwy8NfYxD66vNEL7cMFYgqr2Mai-jOshQv_62Uu4</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Cycle connectivity and cyclic connectivity index of intuitionistic fuzzy graphs1</title><source>EBSCOhost Business Source Complete</source><creator>Gong, Zengtai ; He, Lele</creator><creatorcontrib>Gong, Zengtai ; He, Lele</creatorcontrib><description>Connectivity parameters play a crucial role in network analysis. The cyclic reachability is an important attribute that determines the connectivity of the network, the strength of the cycles in intuitionistic fuzzy graphs (IFGs) is not unique. This article first introduces several concepts of cycle connectivity of IFGs, and then discusses the related properties. On the basis of the cycle connectivity of IFGs, the concepts of cyclic connectivity index ( CCI ) and average cyclic connectivity index ( ACCI ) are proposed, which can be used to express the reachability of cycle. Some results of CCI on IFGs are discussed, such as cutvertices, trees, and complete intuitionistic fuzzy graphs. The vertices of IFGs are divided into three categories according to ACCI . Two algorithms are introduced, one to find CCI and ACCI of a given IFGs and the other to identify the nature of vertices.</description><identifier>ISSN: 1064-1246</identifier><identifier>EISSN: 1875-8967</identifier><identifier>DOI: 10.3233/JIFS-222332</identifier><language>eng</language><ispartof>Journal of intelligent &amp; fuzzy systems, 2023-04, Vol.44 (4), p.6737-6748</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c121t-a7aad1f61494a7ff6ca47dacb69c6b15625286c84bc606566c463f5112a018563</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Gong, Zengtai</creatorcontrib><creatorcontrib>He, Lele</creatorcontrib><title>Cycle connectivity and cyclic connectivity index of intuitionistic fuzzy graphs1</title><title>Journal of intelligent &amp; fuzzy systems</title><description>Connectivity parameters play a crucial role in network analysis. The cyclic reachability is an important attribute that determines the connectivity of the network, the strength of the cycles in intuitionistic fuzzy graphs (IFGs) is not unique. This article first introduces several concepts of cycle connectivity of IFGs, and then discusses the related properties. On the basis of the cycle connectivity of IFGs, the concepts of cyclic connectivity index ( CCI ) and average cyclic connectivity index ( ACCI ) are proposed, which can be used to express the reachability of cycle. Some results of CCI on IFGs are discussed, such as cutvertices, trees, and complete intuitionistic fuzzy graphs. The vertices of IFGs are divided into three categories according to ACCI . Two algorithms are introduced, one to find CCI and ACCI of a given IFGs and the other to identify the nature of vertices.</description><issn>1064-1246</issn><issn>1875-8967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpVkE1Lw0AURQdRsFZX_oHsZXTefLxJlhKsVgoK6jpMXjI6UpOSmYrprzelblzdw-VyF4exSxDXSip187hcvHApJ5RHbAa5NTwv0B5PLFBzkBpP2VmMn0KANVLM2HM50rrNqO-6llL4DmnMXNdkNNWB_veha9qfrPcTpG1Ioe9CTNPIb3e7MXsf3OYjwjk78W4d24u_nLO3xd1r-cBXT_fL8nbFCSQk7qxzDXgEXWhnvUdy2jaOaiwIazAojcyRcl0TCjSIpFF5AyCdgNygmrOrwy8NfYxD66vNEL7cMFYgqr2Mai-jOshQv_62Uu4</recordid><startdate>20230403</startdate><enddate>20230403</enddate><creator>Gong, Zengtai</creator><creator>He, Lele</creator><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20230403</creationdate><title>Cycle connectivity and cyclic connectivity index of intuitionistic fuzzy graphs1</title><author>Gong, Zengtai ; He, Lele</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c121t-a7aad1f61494a7ff6ca47dacb69c6b15625286c84bc606566c463f5112a018563</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gong, Zengtai</creatorcontrib><creatorcontrib>He, Lele</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of intelligent &amp; fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gong, Zengtai</au><au>He, Lele</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cycle connectivity and cyclic connectivity index of intuitionistic fuzzy graphs1</atitle><jtitle>Journal of intelligent &amp; fuzzy systems</jtitle><date>2023-04-03</date><risdate>2023</risdate><volume>44</volume><issue>4</issue><spage>6737</spage><epage>6748</epage><pages>6737-6748</pages><issn>1064-1246</issn><eissn>1875-8967</eissn><abstract>Connectivity parameters play a crucial role in network analysis. The cyclic reachability is an important attribute that determines the connectivity of the network, the strength of the cycles in intuitionistic fuzzy graphs (IFGs) is not unique. This article first introduces several concepts of cycle connectivity of IFGs, and then discusses the related properties. On the basis of the cycle connectivity of IFGs, the concepts of cyclic connectivity index ( CCI ) and average cyclic connectivity index ( ACCI ) are proposed, which can be used to express the reachability of cycle. Some results of CCI on IFGs are discussed, such as cutvertices, trees, and complete intuitionistic fuzzy graphs. The vertices of IFGs are divided into three categories according to ACCI . Two algorithms are introduced, one to find CCI and ACCI of a given IFGs and the other to identify the nature of vertices.</abstract><doi>10.3233/JIFS-222332</doi><tpages>12</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1064-1246
ispartof Journal of intelligent & fuzzy systems, 2023-04, Vol.44 (4), p.6737-6748
issn 1064-1246
1875-8967
language eng
recordid cdi_crossref_primary_10_3233_JIFS_222332
source EBSCOhost Business Source Complete
title Cycle connectivity and cyclic connectivity index of intuitionistic fuzzy graphs1
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T21%3A09%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Cycle%20connectivity%20and%20cyclic%20connectivity%20index%20of%20intuitionistic%20fuzzy%20graphs1&rft.jtitle=Journal%20of%20intelligent%20&%20fuzzy%20systems&rft.au=Gong,%20Zengtai&rft.date=2023-04-03&rft.volume=44&rft.issue=4&rft.spage=6737&rft.epage=6748&rft.pages=6737-6748&rft.issn=1064-1246&rft.eissn=1875-8967&rft_id=info:doi/10.3233/JIFS-222332&rft_dat=%3Ccrossref%3E10_3233_JIFS_222332%3C/crossref%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true