吉林大学学报（理学版）2016，Vol.54Issue(3)：547-552,6.DOI:10.13413/j.cnki.jdxblxb.2016.03.26
融合分层抽样和动态抽样的多状态网络可靠度 M-C 估计算法
M-C Estimation Algorithm for Multistate Network Reliability Based on Fusion of Hierarchical Sampling and Dynamic Sampling
摘要
Abstract
Based on a Monte-Carlo (M-C)estimation algorithm of multi state network reliability,the author considered an M-C estimation algorithm based on fusion of hierarchical sampling and dynamic sampling.The hierarchical sampling was realized by setting the probability threshold α to change hierarchical principle based on the hierarchical sampling method of state tree search.Using dynamic sampling,the capacity value of each side of the network was dynamically generated when the network was invalid,so that the invalid network state could be generated without the sampling of all edges, and the simulation time was shortened.Simulation results show that the dynamic sampling can shorten the simulation time,but the advantage will gradually disappear with the increase of the network reliability,and it is more suitable for the multi state network with low reliability.关键词
网络可靠度/多状态网络/Monte-Carlo 估计Key words
network reliability/multi state network/Monte-Carlo estimation分类
信息技术与安全科学引用本文复制引用
路永华..融合分层抽样和动态抽样的多状态网络可靠度 M-C 估计算法[J].吉林大学学报（理学版）,2016,54(3):547-552,6.基金项目
甘肃省自然科学基金(批准号:1208RJZA105)和甘肃省科技支撑计划项目(批准号:2015GS06607) （批准号:1208RJZA105）
