TY - JOUR
T1 - An information dimension of weighted complex networks
AU - Wen, Tao
AU - Jiang, Wen
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/7/1
Y1 - 2018/7/1
N2 - The fractal and self-similarity are important properties in complex networks. Information dimension is a useful dimension for complex networks to reveal these properties. In this paper, an information dimension is proposed for weighted complex networks. Based on the box-covering algorithm for weighted complex networks (BCANw), the proposed method can deal with the weighted complex networks which appear frequently in the real-world, and it can get the influence of the number of nodes in each box on the information dimension. To show the wide scope of information dimension, some applications are illustrated, indicating that the proposed method is effective and feasible.
AB - The fractal and self-similarity are important properties in complex networks. Information dimension is a useful dimension for complex networks to reveal these properties. In this paper, an information dimension is proposed for weighted complex networks. Based on the box-covering algorithm for weighted complex networks (BCANw), the proposed method can deal with the weighted complex networks which appear frequently in the real-world, and it can get the influence of the number of nodes in each box on the information dimension. To show the wide scope of information dimension, some applications are illustrated, indicating that the proposed method is effective and feasible.
KW - Box-covering algorithm
KW - Information dimension
KW - Weighted complex networks
UR - http://www.scopus.com/inward/record.url?scp=85042940529&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2018.02.067
DO - 10.1016/j.physa.2018.02.067
M3 - 文章
AN - SCOPUS:85042940529
SN - 0378-4371
VL - 501
SP - 388
EP - 399
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -