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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
A Note On Distance-Based Entropy Of Dendrimers, Modjtaba Ghorbani, Matthias Dehmer, Samaneh Zangi, Abbe Mowshowitz, Frank Emmert-Streib
A Note On Distance-Based Entropy Of Dendrimers, Modjtaba Ghorbani, Matthias Dehmer, Samaneh Zangi, Abbe Mowshowitz, Frank Emmert-Streib
Publications and Research
This paper introduces a variant of entropy measures based on vertex eccentricity and applies it to all graphs representing the isomers of octane. Taking into account the vertex degree as well (degree-ecc-entropy), we find a good correlation with the acentric factor of octane isomers. In particular, we compute the degree-ecc-entropy for three classes of dendrimer graphs.
On Properties Of Distance-Based Entropies On Fullerene Graphs, Modjtaba Ghorbani, Matthias Dehmer, Mina Rajabi-Parsa, Abbe Mowshowitz, Frank Emmert-Streib
On Properties Of Distance-Based Entropies On Fullerene Graphs, Modjtaba Ghorbani, Matthias Dehmer, Mina Rajabi-Parsa, Abbe Mowshowitz, Frank Emmert-Streib
Publications and Research
In this paper, we study several distance-based entropy measures on fullerene graphs. These include the topological information content of a graph Ia(G), a degree-based entropy measure, the eccentric-entropy Ifs(G), the Hosoya entropy H(G) and, finally, the radial centric information entropy Hecc. We compare these measures on two infinite classes of fullerene graphs denoted by A12n+4 and B12n+6. We have chosen these measures as they are easily computable and capture meaningful graph properties. To demonstrate the utility of these measures, we investigate the Pearson correlation between them on the fullerene graphs.
Entropy And The Complexity Of Graphs Revisited, Abbe Mowshowitz, Matthias Dehmer
Entropy And The Complexity Of Graphs Revisited, Abbe Mowshowitz, Matthias Dehmer
Publications and Research
This paper presents a taxonomy and overview of approaches to the measurement of graph and network complexity. The taxonomy distinguishes between deterministic (e.g., Kolmogorov complexity) and probabilistic approaches with a view to placing entropy-based probabilistic measurement in context. Entropy-based measurement is the main focus of the paper. Relationships between the different entropy functions used to measure complexity are examined; and intrinsic (e.g., classical measures) and extrinsic (e.g., Körner entropy) variants of entropy-based models are discussed in some detail.