子网络时间分布作为广义随机Petri网多层评价的手段

G. Klas, Reinhard Matuschka
{"title":"子网络时间分布作为广义随机Petri网多层评价的手段","authors":"G. Klas, Reinhard Matuschka","doi":"10.1109/PNPM.1991.238783","DOIUrl":null,"url":null,"abstract":"A new hierarchical evaluation procedure for generalized stochastic Petri nets (GSPN) is being presented. It is based on extensions of flow equivalent aggregation (FEA). At every level of hierarchy, subnets are approximated by substitute networks. As criterion for the similarity of the networks, the subnetwork time distribution (STD) is used which is the sojourn time distribution of a token X in a subnet conditioned on the token distribution at the epoch of arrival of X and the context into which the net is embedded for determining the STD. The computation of a substitute network's type and parameters is outlined. The performance of this technique called FEAD (FEA based on subnetwork time distribution) is discussed by means of examples.<<ETX>>","PeriodicalId":137470,"journal":{"name":"Proceedings of the Fourth International Workshop on Petri Nets and Performance Models PNPM91","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1991-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Subnetwork time distributions as a means for multilevel evaluation of generalized stochastic Petri nets\",\"authors\":\"G. Klas, Reinhard Matuschka\",\"doi\":\"10.1109/PNPM.1991.238783\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new hierarchical evaluation procedure for generalized stochastic Petri nets (GSPN) is being presented. It is based on extensions of flow equivalent aggregation (FEA). At every level of hierarchy, subnets are approximated by substitute networks. As criterion for the similarity of the networks, the subnetwork time distribution (STD) is used which is the sojourn time distribution of a token X in a subnet conditioned on the token distribution at the epoch of arrival of X and the context into which the net is embedded for determining the STD. The computation of a substitute network's type and parameters is outlined. The performance of this technique called FEAD (FEA based on subnetwork time distribution) is discussed by means of examples.<<ETX>>\",\"PeriodicalId\":137470,\"journal\":{\"name\":\"Proceedings of the Fourth International Workshop on Petri Nets and Performance Models PNPM91\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fourth International Workshop on Petri Nets and Performance Models PNPM91\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PNPM.1991.238783\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fourth International Workshop on Petri Nets and Performance Models PNPM91","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PNPM.1991.238783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

提出了一种新的广义随机Petri网(GSPN)分级评价方法。它是基于流动等效聚集(FEA)的扩展。在每一层次结构中,子网都是由替代网络近似表示的。采用子网时间分布(STD)作为判定网络相似性的标准,即令牌X在子网中的停留时间分布,该时间分布取决于令牌X到达时间点的分布和网络所处的环境,并给出了替代网络类型和参数的计算方法。通过实例讨论了基于子网时间分布的FEAD (FEA based on subnetwork time distribution)技术的性能
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Subnetwork time distributions as a means for multilevel evaluation of generalized stochastic Petri nets
A new hierarchical evaluation procedure for generalized stochastic Petri nets (GSPN) is being presented. It is based on extensions of flow equivalent aggregation (FEA). At every level of hierarchy, subnets are approximated by substitute networks. As criterion for the similarity of the networks, the subnetwork time distribution (STD) is used which is the sojourn time distribution of a token X in a subnet conditioned on the token distribution at the epoch of arrival of X and the context into which the net is embedded for determining the STD. The computation of a substitute network's type and parameters is outlined. The performance of this technique called FEAD (FEA based on subnetwork time distribution) is discussed by means of examples.<>
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信