摘要
针对随机流网络可靠性建模难的问题,提出一种基于粗糙集和Petri网相结合的随机流网络可靠性评价方法.建立了随机流网络在确定网络状态下的Petri网模型,并利用粗糙集方法求得网络中各边状态对系统状态的重要度;然后以此作为随机流网络的Petri网模型中各变迁的优先因子来控制模型中变迁的激发;最后通过蒙特卡罗仿真求得随机流网络可靠度的估计值.仿真结果表明,该方法是一种计算随机流网络可靠性的有效方法.
Aiming at the practical conditions of stochastic flow network system,a combined method for estimating the reliability based on rough sets theory and Petri nets is proposed.The Petri net model for the corresponding weighted graph of a certain network state is constructed.Then the importance indexes of each arc states to the system state are obtained from the knowledge base by applying the rough sets theory,which can be regarded as the priority index of transitions in the Petri net model.Therefore,the firing of transitions in the model can be controlled.Finally,the Monte-Carlo method is used to obtain the estimated reliability of stochastic flow network system.Simulation results show that the combined method is efficient to calculate the reliability of stochastic flow network system.
出处
《控制与决策》
EI
CSCD
北大核心
2010年第8期1273-1276,1280,共5页
Control and Decision
基金
国家自然科学基金项目(60774029)
关键词
随机流网络
粗糙集
PETRI网
可靠性
Stochastic flow network
Rough sets theory
Petri nets
Reliability
