【摘要】 随机Petri网(SPN)是一种有力的系统建模和分析工具。但SPN在应用中经常碰到状态空间爆炸问题。分解压缩技术是解决随机网状态空间指数性增长的有效方法之一。介绍了一种获得SPN可靠性模型瞬时状态的分解方法。该方法在保证评价和预测可靠性精确度的基础上,不仅能有效地降低可靠性描述与分析的复杂度,还扩大了分解压缩技术的适用范围。更多还原

【Abstract】 The stochastic Petri net (SPN) is one kind of forceful implements which build and analyze the system models. But, the major drawback of SPN models is the state space explosion with increasing model complexity. The decomposition technique is one of the effective methods that resolve the exponent increase of state space. One kind of the decomposition method to obtain an approximate transient state solution of large SPN performance models of complex systems is introduced. It is shown that the suggested method ensure the precision of appraising and forecasting reliability, reduce the complicated degree of describing and analyzing the software reliability effectively, and expand the applicability of decomposition techniques.更多还原