A local-world evolving hypernetwork model
Complex hypernetworks are ubiquitous in the real system. It is very important to investigate the evolution mecha- nisms. In this paper, we present a local-world evolving hypernetwork model by taking into account the hyperedge growth and local-world hyperedge preferential attachment mechanisms. At ea...
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| Published in | Chinese physics B Vol. 23; no. 1; pp. 532 - 538 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-1056 2058-3834 |
| DOI | 10.1088/1674-1056/23/1/018901 |
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| Abstract | Complex hypernetworks are ubiquitous in the real system. It is very important to investigate the evolution mecha- nisms. In this paper, we present a local-world evolving hypernetwork model by taking into account the hyperedge growth and local-world hyperedge preferential attachment mechanisms. At each time step, a newly added hyperedge encircles a new coming node and a number of nodes from a randomly selected local world. The number of the selected nodes from the local world obeys the uniform distribution and its mean value is m. The analytical and simulation results show that the hyperdegree approximately obeys the power-law form and the exponent of hyperdegree distribution is 7 = 2 ＋ 1/m. Furthermore, we numerically investigate the node degree, hyperedge degree, clustering coefficient, as well as the average distance, and find that the hypemetwork model shares the scale-flee and small-world properties, which shed some light for deeply understanding the evolution mechanism of the real systems. |
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| AbstractList | Complex hypernetworks are ubiquitous in the real system. It is very important to investigate the evolution mecha- nisms. In this paper, we present a local-world evolving hypernetwork model by taking into account the hyperedge growth and local-world hyperedge preferential attachment mechanisms. At each time step, a newly added hyperedge encircles a new coming node and a number of nodes from a randomly selected local world. The number of the selected nodes from the local world obeys the uniform distribution and its mean value is m. The analytical and simulation results show that the hyperdegree approximately obeys the power-law form and the exponent of hyperdegree distribution is 7 = 2 ＋ 1/m. Furthermore, we numerically investigate the node degree, hyperedge degree, clustering coefficient, as well as the average distance, and find that the hypemetwork model shares the scale-flee and small-world properties, which shed some light for deeply understanding the evolution mechanism of the real systems. |
| Author | 杨光勇 刘建国 |
| AuthorAffiliation | Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, China |
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| Notes | Yang Guang-Yong Liu Jian-Guo（ Research Center of Complex Systems Science, University of Shanghai l＇or Science and Technology, Shanghai 200093, China） 11-5639/O4 |
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| Title | A local-world evolving hypernetwork model |
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