故障树随机生成及变量排序  

Random generation and variable ordering of fault tree

作　　者：莫毓昌[1,2] 杨全胜[2] 

机构地区：[1]浙江师范大学数理信息学院,浙江金华321004 [2]东南大学计算机科学与工程学院,江苏南京210096

出　　处：《浙江大学学报（工学版）》2011年第9期1539-1543,共5页Journal of Zhejiang University：Engineering Science

基　　金：国家自然科学基金资助项目(60903011);高等学校博士学科点专项科研基金资助项目(20090092120030);江苏省自然科学基金资助项目(BK2009267);浙江省自然科学基金资助项目(Y1100689)

摘　　要：针对故障树分析方法性能评价研究中存在的测试基准规模和多样性问题,基于故障树样本随机生成的思想,确定了故障树6个主要结构特征,并依据这些结构特征给出了自顶向下地生成算法,包括随机树骨架生成算法和随机重复度叶子序列生成算法.通过变量排序策略性能评价给出了测试基准的示范应用.性能评价表明:深度策略(DEEP)性能远优于广度策略(WIDE);WIDE策略的优越性依赖于重复叶子节点数量;改进带权值深度策略(WDEEP)是DEEP策略的互补策略并不能够代替DEEP策略.To cope with the problems related to benchmark size and diversity for performance evaluation of fault tree analysis methods,based on the idea of random generation of fault trees,this work proposed six important structural characteristic parameters of various fault trees,a top-down generation algorithm according to these parameters,which included a random tree skeleton generation algorithm and a randomly repeated leaf sequence generation algorithm,then illustrated the benchmark application with variable ordering heuristic performance evaluation.The evaluation shows that： deep（DEEP） heuristic is far superior to the wide（WIDE） heuristic;the superiority of the WIDE heuristic depends on the number of repeated leaves in the fault tree;improved weighting deep（WDEEP） heuristic is a complementary strategy for DEEP heuristic and not able to replace it.

关 键 词：故障树 测试基准 变量排序 二进制决策图 

分 类 号：TB114[理学—概率论与数理统计]