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dc.contributor.authorMahapatra, R.en_AU
dc.contributor.authorSamanta, S.en_AU
dc.contributor.authorPal, M.en_AU
dc.contributor.authorLee, J.-G.en_AU
dc.contributor.authorKhan, S.K.en_AU
dc.contributor.authorNaseem, U.en_AU
dc.contributor.authorBhadoria R.S.en_AU
dc.date.accessioned2021-06-02T04:55:29Z
dc.date.available2021-06-02T04:55:29Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/2123/25336
dc.description.abstractGraph colouring is the systemof assigning a colour to each vertex of a graph. It is done in such a way that adjacent vertices do not have equal colour. It is fundamental in graph theory. It is often used to solve real-world problems like traffic light signalling, map colouring, scheduling, etc. Nowadays, social networks are prevalent systems in our life. Here, the users are considered as vertices, and their connections/interactions are taken as edges. Some users follow other popular users' profiles in these networks, and some don't, but those non-followers are connected directly to the popular profiles. That means, along with traditional relationship (information flowing), there is another relation among them. It depends on the domination of the relationship between the nodes. This type of situation can be modelled as a directed fuzzy graph. In the colouring of fuzzy graph theory, edge membership plays a vital role. Edge membership is a representation of flowing information between end nodes of the edge.Apart fromthe communication relationship, theremay be some other factors like domination in relation. This influence of power is captured here. In this article, the colouring of directed fuzzy graphs is defined based on the influence of relationship. Along with this, the chromatic number and strong chromatic number are provided, and related properties are investigated. An application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.en_AU
dc.language.isoenen_AU
dc.subjectCOVID-19en_AU
dc.subjectCoronavirusen_AU
dc.titleColouring of COVID-19 Affected Region Based on Fuzzy Directed Graphsen_AU
dc.typeArticleen_AU
dc.identifier.doi10.32604/cmc.2021.015590
dc.relation.otherNational Research Foundation of Korea, NRF Kementerian Pendidikan Malaysia, KPM: 2018R1D1A1B07049321en_AU


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