Relevant Researches On Evolutionary Models And Dynamical Features Of General Transportation Networks

To characterize the structure complexity, evolutionary mechanisms and dynamic behaviors of network is the key in researching transportation network. In this paper, by using the theoretical analysis and numerical simulations, we studied the evolution and dynamical behaviors on general transportation networks in the statistical mechanics point of view.Firstly, we made a series researches on the weighted models of general transportation networks. By considering the statistical properties of transportation networks, such as degree distribution, strength distribution, weight distribution, correlation of strength and degree, clustering coefficient and assortativity, and so on, we evolved some weighted networks models. The different evolution processes can give various statistical features of real transportation systems successfully. Especially, the models can reproduce features such as saturation for small variables, exponential decay, etc.At the beginning of the research on the complex network science, people focus on the small world effect, scale free phenomena, hierarchy architecture, modularity structure, and so on. With the deeper insight into this field, people begin to realize the hidden features and structures of networks. In this paper, we studied the statistical characteristics of Hub nodes in various important levels, and to reveal the main structures of transportation networks in the nodes' importance point of view.Epidemic dynamic is one of the most important problems in transpiration network science. By considering the modular structure and small world property of real transportation system, we study the effect of modularity on the epidemic behaviors on networks. It is found that the modularity prevent the rate, extent and the synchronization behavior of the propagation. It reveals some implicit regularities of the relationship between the modularity and the epidemic spreading dynamics.Cascading failures can take place in large transportation networks, such as power grid, Internet, etc, sometimes. It may bring catastrophe of the whole system. How to defend the cascade break down is one of the most important problems in researching network science. In this paper, we investigate the cascading failure by considering the degree based navigation strategy. It is found that by using the proper navigation strategy, it can reduce the risk of cascading failure considerably.In addition, we investigate the statistical properties of the traffic dynamics in equilibrium state on transportation networks with different topology, including regular,random, small world and scale free networks. To understand the properties in trafficequilibrium state is important in realizing the traffic phenomena of real transportationsystems.