Volume Dimension of Mass Functions in Complex Networks

A novel definition of volume dimension for a mass function based on a sigmoid asymptote is proposed; in particular, we extend the volume dimension of a mass function to define the volume dimensions for nodes and edges in complex networks. Furthermore, the relationship between the proposed volume dimension and the non-specificity term of the Deng entropy is shown, and the traditional volume dimension and volume dimension based on the node degree in complex networks are revisited. Our experiments show that in both real and synthetic complex networks, the volume dimension tends to follow a sigmoidal asymptote rather than the previously utilized power law asymptote.

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Publication Details

Journal
Mathematics
Published
2025-08-28
DOI
https://doi.org/10.3390/math13172775
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Volume Dimension of Mass Functions in Complex Networks

Aldo Ramírez-Arellano, Jazmin-Susana De-la-Cruz-García, Juan Bory Reyes, Maria del Carmen Soto-Camacho
Mathematics
Complex Network Analysis Techniques
article

Volume Dimension of Mass Functions in Complex Networks

Aldo Ramírez-Arellano, Jazmin-Susana De-la-Cruz-García, Juan Bory Reyes, Maria del Carmen Soto-Camacho
article en

Abstract

A novel definition of volume dimension for a mass function based on a sigmoid asymptote is proposed; in particular, we extend the volume dimension of a mass function to define the volume dimensions for nodes and edges in complex networks. Furthermore, the relationship between the proposed volume dimension and the non-specificity term of the Deng entropy is shown, and the traditional volume dimension and volume dimension based on the node degree in complex networks are revisited. Our experiments show that in both real and synthetic complex networks, the volume dimension tends to follow a sigmoidal asymptote rather than the previously utilized power law asymptote.

MathematicsVol. 13(17)
Instituto Politécnico Nacional (MX)
Instituto Politécnico Nacional
Openalex Percentile: Top 82%
Complex Network Analysis Techniques
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