中文摘要：

我们在评估平行系统的表演分析随机的 Petri 捕捞的通常分布式的时间转变(GDTT_SPN ) 的缺点，并且建议一个更多的一般模型，随机的单个谓词 / 转变网(SIPTN ) 。SIPTN 让更高的建模，在 SIPTN 与 GDTT_SPN 相比驱动并且能提供更多的实际模式，实际模型逗留时间分发不仅被转变，而且由个人决定。GDTT_SPN 是 SIPTN 的一个子集，这进一步被证明。当 SIPTN 介绍从谓词 / 转变网络合拢技术， SIPTN 模型有更简单、更直觉的图形的符号和因此更高的可用性，并且因此对为平行系统构造模拟模式合适。

英文摘要：

We analyze the drawbacks of generally distributed time transition stochastic Petri nets （GDTT_SPN） in evaluating the performance of parallel systems, and propose a more general model, stochastic individual predicate/transition nets （SIPTN）. SIPTN has higher modeling power and could provide more realistic models compared to GDTT_SPN, because in SIPTN the sojourn time distribution is determined not only by the transition, but also by the individuals. It is further proved that GDTT_SPN is a subset of SIPTN. As SIPTN introduces folding techniques from predicate/transition nets, SIPTN models have simpler and more intuitive graphic notations and accordingly higher usability, and thus are suitable for constructing simulation models for parallel systems.