Research On Evolving Model Of Complex Network

Complex networks have seen much interest from all research circles and have found many potential applications in a variety of fields. Yet despite the importance and pervasiveness of networks, scientists have had little understanding of their structure and properties. It is known to us all, randomness is in line with the major features of real-life networks, while deterministicness makes it easier to gain a visual understanding of how networks are shaped, and how do different nodes relate to each other. Therefore, it would be not only of major theoretical interest but also of great practical significance. Especially, evolving models can not only capture correctly the processes that assembled the networks but also help to know how various microscopic processes influence the network topology. These studies can lead us to master the function of network and design of reasonable network.This paper keep general method of modeling to apply the theory of complex network into DaLian Public transportation systems based on the real-life network. The vertex which is defined as some stations in some important areas is the bus stop of DaLian. The edge is carrying corporation between two bus stations. The public transportation network is researched through complex networks theory in order to get topology and some network properties , such as degree distribution, clustering coefficient, average shortest path length, degree assortativity and node betweenness. We find that DaLian public transportation is a scale-free and small-world network.This paper also proposes two extended model based on the analysis of real-life work. Some nodes of network is characterized by a critical load (or flow, capacity, etc.), which is taken into the first model account, thus introducing the constant K_max as the maximum degree. Therefore, we improved the preferential attachment of BA model. In some condition, our model is the same as the BA model. By means of numerical simulation, the degree distribution of our model does not follow power-law distribution, and the time-evolution has been changed in terms of introducing new pa-...