Composite Complex Network Model Research And Application

Many complex systems in nature and human society can be described as complex networks. Complex interaction exists between the structure and function of complex systems. Most of traditional researches only involve local subsystems and signal relationship generated among individuals with same property, which results in a lot of difficult when describing the whole complex network. Thus, researching the network model on how to describe the complex systems in a form with variety of elements and their complex relationships has important theoretical significance and application value. Based on this, this paper studied composite complex network model, providing new research tools and methods to the study of complex systems. The results of innovative research are shown as follows:1. A composite complex network model is proposed. This model is consists of several sub-networks and their connections. In that form, relationships among different elements in the same complex network, in different complex networks and relationships between different complex networks are given.2. Based on this new model, analyzing methods are presented. By adopting network computing, intrinsic properties of complex networks is remained. And the problems of existing many difficult in analyzing huge complex network are solved by adopting network computing. By defining function of sub-network, the process of constructing the complex network is simplified. And function of denegation makes observer could analyze this complex network in special sub-network.3. Based on the above composite complex networks and network operating definitions and theorems, two kinds of network evolution models are proposed from the angle of practical problems. One is evolution model of complex network composing of two sub-systems. Degree distributions in these two models both obey the power law. Another is the model for one subsystem network whose node and links with pure features, its nodes have maximum degree restriction and its nodes links have local and global linkage mechanisms, the theory analysis and numeric simulation all show that its degree distribution obey the Mandelbrot distribution.4. Connection coefficient focusing on closeness of composite complex network is defined. By adopting propagating mechanism, information vector is given. Based on these definitions a algorithm of detecting community in composite complex network is proposed. The experiments show its validity.5. For testifying this model, empirical analysis are given by taking airline and railway compositing networks. By statistics analysis, degree distribution, average path length, efficiency and connection coefficient are discussed. In addition, harness of this composite complex network is given. At last, transferring and routing are researched. Several advice are given in order to improve the performance of this transport network.