A Hybrid Approach in Intelligent Workflow Modelling Using Petri Nets and Neural Network for Inter-Organizational Cooperation
With business applications going towardcollectivization, inter-organization, internationalization,many researches have been launched about intelligentworkflow for inter-organizational cooperation. Petrinets are powerful and versatile tools for modeling,simulating, analyzing and designing of complexworkflow systems. This paper mainly discusses a hybridapproach using neural network and Petri nets in theformal model of intelligent workflow for inter-organizational cooperation. The model is calledIntelligent Neural Extended Petri Nets (INEPN). INEPNnot only takes the descriptive advantages of Petri nets,but also has learning ability like neural network.INEPN is suitable for dynamic process and information,I.e., the weights of INEPN are adjustable. Based onINEPN, an intelligent WfMS is developed for rater-organizational cooperation in manufacturing industry.The INEPN model is an innovative method forintelligent workflow.The static, centralized, sequential, closed, over-the-wall models of the exclusively-competitive world are one-by one replaced by dynamic distributed, parallel,open cooperative strategies calling for new organizational paradigms supporting globalization of all aspects of life1.Workflow Mangement Systems(WfMS) are proliferated through the computer supported cooperative work (CSCW)systems.
Xiaoqiang Wu
School of Economics & Management,Beijing University of Aeronautics & Astronautics,Beijing,100083,P.R.China
国际会议
厦门
英文
307-311
2004-05-26（万方平台首次上网日期，不代表论文的发表时间）