Open AccessResearch on related properties of two types of self-similar networks
Author(s) -
Zhong Wang,
Mafuxiang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1634/1/012030
Subject(s) - similarity (geometry) , fractal , complex network , self similarity , property (philosophy) , computer science , type (biology) , degree distribution , mathematics , theoretical computer science , artificial intelligence , topology (electrical circuits) , combinatorics , mathematical analysis , epistemology , ecology , philosophy , geometry , image (mathematics) , biology
Self-similarity is the whole and the part of a complex system, that is, the similarity of structure or property between the part and that part. Studying self-similar networks is helpful for us to better understand the complex networks in the real world. Because the fractal networks have self-similarity, a type of modified Koch network and a type of Austria network were firstly described by this paper, and the exact expressions of degree distribution and aggregation coefficient of the two types of networks were secondly derived, finally, the relationship between the Randic indicator of the two types of network and other invariants is studied.