Intersection soft ideals and their quotients on KU-algebras

Ansari, Moin A.; Koam, Ali N. A.; Haider, Azeem

doi:10.3934/math.2021700

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…Example 2.4. [17] With P = {1, 2, 3, 4, 5, 6} we construct the following table: It is clear that (P, , 1) is a JU-algebra, A = {1, 2} and B = {1, 2, 3, 4, 5} are ideals of JU-algebra P.…”

Section: Definition 23mentioning

confidence: 99%

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On Some Graphs Based on the Ideals of JU-Algebras

Hakami,

Ansari,

Haider

2024

Int. J. Anal. Appl.

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“…Example 2.4. [17] With P = {1, 2, 3, 4, 5, 6} we construct the following table: It is clear that (P, , 1) is a JU-algebra, A = {1, 2} and B = {1, 2, 3, 4, 5} are ideals of JU-algebra P.…”

Section: Definition 23mentioning

confidence: 99%

“…In a consequence of works based on different logical algebras, Moin [16] studied rough set theory on JU-algebras, whereas Moin et al [17] introduced JU-algebras and p-closure ideals. Whereas Usman et al [20] introduced pseudo valuations and their metric on JU-algebras.…”

Section: Introductionmentioning

confidence: 99%

On Some Graphs Based on the Ideals of JU-Algebras

Hakami,

Ansari,

Haider

2024

Int. J. Anal. Appl.

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“…In this paper, motivated by [7], [8], [23], [28], [29], and [30], by Laplacian spectrums, we characterized an explicit closed-form formula for the GMFPT of HM n .…”

mentioning

confidence: 99%

Matrix Analysis of Hexagonal Model and Its Applications in Global Mean-First-Passage Time of Random Walks

Zaman²,

Ullah

et al. 2023

IEEE Access

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Recent advances in graph-structured learning have demonstrated promising results on the graph classification task. However, making them scalable on huge graphs with millions of nodes and edges remains challenging due to their high temporal complexity. In this paper, by the decomposition theorem of Laplacian polynomial and characteristic polynomial we established an explicit closed-form formula of the global meanfirst-passage time (GMFPT) for hexagonal model. Our method is based on the concept of GMFPT, which represents the expected values when the walk begins at the vertex. GMFPT is a crucial metric for estimating transport speed for random walks on complex networks. Through extensive matrix analysis, we show that, obtaining GMFPT via spectrums provides an easy calculation in terms of large networks.INDEX TERMS Hexagonal model, Laplacian polynomial, decomposition theorem, GMFPT. I. INTRODUCTIONInteractions between pairs of entities occur every day in real-world systems. Human interaction, financial systems, recommender systems, social networks, road networks, and networks of protein interactions are examples of such systems. In graph theory, these pairs of entities are called a network, in which the substances are vertices and the communication between any two substances are an edge [6]. Networks have rich applications in classical grid-structured data, such as photographs, to speed up calculations. The graph-structural data is useful in encoding networks of low-dimensional embeddings for classic machine learning and data mining algorithms [3]. Researchers follow this strategy to handle complex graph problems, such as graph categorization. The network arrangement problem is concerned with categorizing complicated network structures into multiple groups. It has many real-life phenomena, includingThe associate editor coordinating the review of this manuscript and approving it for publication was Engang Tian .

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Intersection soft ideals and their quotients on KU-algebras

Cited by 2 publications

References 16 publications

On Some Graphs Based on the Ideals of JU-Algebras

On Some Graphs Based on the Ideals of JU-Algebras

Matrix Analysis of Hexagonal Model and Its Applications in Global Mean-First-Passage Time of Random Walks

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