TY - JOUR
T1 - Analysis on topological features of deterministic hierarchical complex network
AU - Li, Kai
AU - Wu, Wei
AU - He, Yongfeng
AU - Liu, Fusheng
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/6/15
Y1 - 2019/6/15
N2 - Real complex networks usually have small-world effect, scale-free features and hierarchical modularity, a construction method for deterministic hierarchical network is proposed in this paper. The network model with growth and global preferential attachment characteristic and connected by the copy network modules to establish hierarchical network model. By theoretical calculation and numerical simulation about the deterministic hierarchical complex network model, the results illustrate that the complex network model satisfy the small-world effect, scale-free feature and hierarchical modularity, the calculation results show that the size of the hierarchical network model for exponential growth with the network size increased, and the average degree of nodes is shown as linear growth; at the same time, the model of scale-free feature and the hierarchical modularity with network parameters do not have correlation which is an inherent attribute of network model itself; the clustering-degree correlations in the network model satisfy power-law characteristics and the nodes contact closely together in the modules which are connected by the Hub nodes in the complex network model..
AB - Real complex networks usually have small-world effect, scale-free features and hierarchical modularity, a construction method for deterministic hierarchical network is proposed in this paper. The network model with growth and global preferential attachment characteristic and connected by the copy network modules to establish hierarchical network model. By theoretical calculation and numerical simulation about the deterministic hierarchical complex network model, the results illustrate that the complex network model satisfy the small-world effect, scale-free feature and hierarchical modularity, the calculation results show that the size of the hierarchical network model for exponential growth with the network size increased, and the average degree of nodes is shown as linear growth; at the same time, the model of scale-free feature and the hierarchical modularity with network parameters do not have correlation which is an inherent attribute of network model itself; the clustering-degree correlations in the network model satisfy power-law characteristics and the nodes contact closely together in the modules which are connected by the Hub nodes in the complex network model..
KW - Deterministic hierarchical network
KW - Growth
KW - Hierarchical modularity
KW - Preferential attachment
KW - Scale-free feature
KW - Small-world effect
UR - http://www.scopus.com/inward/record.url?scp=85064076090&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2019.03.111
DO - 10.1016/j.physa.2019.03.111
M3 - Article
AN - SCOPUS:85064076090
SN - 0378-4371
VL - 524
SP - 169
EP - 176
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -