2022
DOI: 10.1088/1742-6596/2157/1/012012
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On resolving efficient domination number of path and comb product of special graph

Abstract: We use finite, connected, and undirected graph denoted by G. Let V (G) and E(G) be a vertex set and edge set respectively. A subset D of V (G) is an efficient dominating set of graph G if each vertex in G is either in D or adjoining to a vertex in D. A subset W of V (G) is a resolving set of G if any vertex in G is differently distinguished by its representation respect of every vertex in an ordered set W. Let W = {w 1, w 2, w 3, …, wk } b… Show more

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Cited by 4 publications
(1 citation statement)
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“…The GNN technique adopts the Convolutional Neural Networks (CNN) framework [10] many methods of applying CNN are useful for studying discriminatory features, which have played an important role in increasing the accuracy of the classification of a problem [11]. Some uses of CNN introduce hidden convolution and layer pooling to identify spatially localized features via a set of receptive fields in the kernel form [12] (Fig.…”
Section: Introductionmentioning
confidence: 99%
“…The GNN technique adopts the Convolutional Neural Networks (CNN) framework [10] many methods of applying CNN are useful for studying discriminatory features, which have played an important role in increasing the accuracy of the classification of a problem [11]. Some uses of CNN introduce hidden convolution and layer pooling to identify spatially localized features via a set of receptive fields in the kernel form [12] (Fig.…”
Section: Introductionmentioning
confidence: 99%