Construction and analysis of interdependent networks based on time series and horizontal visibility graphs

In this paper, the construction and statistical features of the directional complex networks with interdependencies (i.e. interdependent networks) are investigated, in which the intra-structure of each sub-network is not considered. Based on time series and horizontal visibility graph, two new visibility model methods are presented: many-to-many directional horizontal visibility algorithm and one-to-one directional horizontal visibility algorithm. Using R software, the interdependent structure of the directional interdependent network constructed by these two algorithms are analyzed and the statistical features are evaluated associated with two periodic time series, a periodic time series and a fractal time series, a periodic time series and a random series, separately. The results show that both algorithms ensure the simplicity of the interdependent structure of the networks and inherit the morphological characteristics of the time series.