考虑共因失效和负载分担的表决系统维修优化分析

随着仪器设备的大型化、精密型和复杂化，传统的单一故障模型很难精确地描述系统。针对可修的表决系统，考虑了负载分担和共因失效两种失效模式，提出了不完美的故障检测策略，并对模型进行了可靠性和维修性分析，求得了系统的瞬时可用度、稳态可用度和平均维修费用。最后通过数值案例给出了同时考虑可用度和维修费用的最优检测策略，能够为设备管理者提供决策依据。     

Analysis of the Chinese air route network as a complex network

The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network (CARN) within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network (CAN). Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.     

An improved genetic algorithm with dynamic topology

The genetic algorithm(GA) is a nature-inspired evolutionary algorithm to find optima in search space via the interaction of individuals. Recently, researchers demonstrated that the interaction topology plays an important role in information exchange among individuals of evolutionary algorithm. In this paper, we investigate the effect of different network topologies adopted to represent the interaction structures. It is found that GA with a high-density topology ends up more likely with an unsatisfactory solution, contrarily, a low-density topology can impede convergence. Consequently, we propose an improved GA with dynamic topology, named DT-GA, in which the topology structure varies dynamically along with the fitness evolution. Several experiments executed with 15 well-known test functions have illustrated that DT-GA outperforms other test GAs for making a balance of convergence speed and optimum quality. Our work may have implications in the combination of complex networks and computational intelligence.