Show simple item record

dc.contributor.authorJamil, Faiza
dc.contributor.authorKashi, Agha
dc.contributor.authorZafar, Sohail
dc.contributor.authorOjiema, Michael Onyango
dc.date.accessioned2023-09-12T11:51:51Z
dc.date.available2023-09-12T11:51:51Z
dc.date.issued2023-05-05
dc.identifier.urihttps://doi.org/10.1155/2023/3635342
dc.identifier.urihttps://www.hindawi.com/journals/complexity/2023/3635342/
dc.identifier.urihttp://ir-library.mmust.ac.ke:8080/xmlui/handle/123456789/2264
dc.description.abstractFractional variants of distance-based parameters have application in the fields of sensor networking, robot navigation, and integer programming problems. Complex networks are exceptional networks which exhibit significant topological features and have become quintessential research area in the field of computer science, biology, and mathematics. Owing to the possibility that many real-world systems can be intelligently modeled and represented as complex networks to examine, administer and comprehend the useful information from these real-world networks. In this paper, local fractional strong metric dimension of certain complex networks is computed. Building blocks of complex networks are considered as the symmetric networks such as cyclic networks , circulant networks , mobious ladder networks , and generalized prism networks . In this regard, it is shown that LSFMD of and is 1 when is even and when is odd, whereas LSFMD of is 1 when is odd and when is even. Also, LSFMD of is where and .en_US
dc.language.isoenen_US
dc.publisherComplexityen_US
dc.subjectLocal Fractional Strong Metric Dimension of Certain Complex Networksen_US
dc.titleLocal Fractional Strong Metric Dimension of Certain Complex Networksen_US
dc.typeArticleen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record