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With the increasing complexity and demand for transportation networks, effective routing planning has attracted more and more attention. Different modes of transportation, such as the airplane, railway and so on, work together, forming a multi-modal transportation network. Therefore, this paper studies the routing and congestion problems in the multi-modal transportation network, and shows how to increase the network capacity as much as possible while saving time and economic costs, so as to avoid congestion and realize the effective use of different modes of transportation. This paper simulates the influence of two main factors on the network capacity, the parameter which shows the importance between time costs and economic costs, and the difference between different transportation modes. The results show the change of the network capacity when the time cost and economic cost are of different importance. There exists a critical point that can balance time costs and economic costs, so as to maximize network capacity. Then this paper further finds out the method of estimating the condition when the network takes the maximum capacity through theoretical analysis. [ABSTRACT FROM AUTHOR]

The network infrastructures, such as the power grids and Internet, are expanding in size due to the increasing needs of our society. This brings about the problem of expanding networks with a guarantee of robustness against network disturbances that may cause catastrophic consequences. In this paper, we study the optimal network expansion in terms of network robustness against cascading failures. Specifically, we consider the network expansion as a Markovian decision process and further propose a reinforcement learning based network expansion method. Simulation results in model networks and real-world networks demonstrate that our expansion method can greatly improve network robustness. Our work provides some insights for the optimal expansion of network infrastructures. [ABSTRACT FROM AUTHOR]

Many real-world networks are interconnected with each other. In this paper, we study the traffic dynamics in interconnected complex networks under an intentional attack. We find that with the shortest time delay routing strategy, the traffic dynamics can show the stable state, periodic, quasi-periodic and chaotic oscillations, when the capacity redundancy parameter changes. Moreover, compared with isolated complex networks, oscillations always take place in interconnected networks more easily. Thirdly, in interconnected networks, oscillations are affected strongly by the coupling probability and coupling preference. [ABSTRACT FROM AUTHOR]

Multipath performance is an important consideration for chaos-based communication systems. In this letter, the performance of the FM-DCSK communication system over multipath fading channels is evaluated by computer simulations. Both Rayleigh fading and Ricean fading are considered, and the low-pass equivalent model of the FM-DCSK system is used in the simulation. Based on this model, we analyze the bit error performance of the system and the effects of system parameters on the bit-error performance. [ABSTRACT FROM AUTHOR]

This paper investigates the driving synchronization of spatiotemporal chaos. Using this method, synchronization could be achieved efficiently. By improving the driving sequence generation method, the spatial periodicity in the original system is overcome. Large quantities of chaotic sequences are available, which possess the excellent properties expected in Code Division Multiple Access (CDMA) communications. These chaotic sequences can be used as the spreading sequences in place of the traditional pseudo-noise sequences. We also evaluate the performance of the chaotic CDMA communication systems and compute the average bit error rate caused by the multi-user interference and the noise in the channel. The theoretical and simulation results show the excellent performance of the scheme. [ABSTRACT FROM AUTHOR]