首页> 外文期刊>Expert Systems with Application >Extended event-condition-action rules and fuzzy Petri nets based exception handling for workflow management
【24h】

Extended event-condition-action rules and fuzzy Petri nets based exception handling for workflow management

机译:扩展的事件条件操作规则和基于模糊Petri网的异常处理,用于工作流管理

获取原文
获取原文并翻译 | 示例

摘要

Exception handling plays a key role in dynamic workflow management that enables streamlined business processes. Handling application-specific exceptions is a knowledge-intensive process involving different decision-making strategies and a variety of knowledge, especially much fuzzy knowledge. Current efforts in workflow exception management are not adequate to support the knowledge-based exception handling. This paper proposes a hybrid exception handling approach based on two extended knowledge models, i.e., generalized fuzzy event-condition-action (GFECA) rule and typed fuzzy Petri net extended by process knowledge (TFPN-PK). The approach realizes integrated representation and reasoning of fuzzy and non-fuzzy knowledge as well as specific application domain knowledge and workflow process knowledge. In addition, it supports two handling strategies, i.e., direct decision and analysis-based decision, during exception management. The approach fills in the gaps in existing related researches, i.e., only providing the capability of direct exception handling and neglecting fuzzy knowledge. Based on TFPN-PK, a weighted fuzzy reasoning algorithm is designed to address the reasoning problem of uncertain goal propositions and known goal concepts by combining forward reasoning with backward reasoning and therefore to facilitate cause analysis and handling of workflow exceptions. A prototype system is developed to implement the proposed approach.
机译:异常处理在可简化业务流程的动态工作流管理中起着关键作用。处理特定于应用程序的异常是一个知识密集型过程,涉及不同的决策策略和各种知识,尤其是很多模糊的知识。当前在工作流异常管理中的努力不足以支持基于知识的异常处理。本文提出了一种基于两种扩展知识模型的混合异常处理方法,即广义模糊事件条件行动(GFECA)规则和由过程知识扩展的类型化模糊Petri网(TFPN-PK)。该方法实现了模糊和非模糊知识以及特定的应用领域知识和工作流过程知识的集成表示和推理。另外,它在异常管理期间支持两种处理策略,即直接决策和基于分析的决策。该方法填补了现有相关研究中的空白,即仅提供直接异常处理和忽略模糊知识的能力。基于TFPN-PK,设计了加权模糊推理算法,通过结合前向推理和后向推理来解决不确定目标命题和已知目标概念的推理问题,从而简化了工作流异常的原因分析和处理。开发了原型系统来实施所提出的方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号