By Topic

A hybrid approach in intelligent workflow modelling using Petri nets and neural network for inter-organizational cooperation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Xiaoqiang Wu ; Sch. of Econ. & Manage., Beijing Univ. of Aeronaut. & Astronaut., China

With business applications' going toward collectivization, interorganization, internationalization, many researches have been launched about intelligent workflow for interorganizational cooperation. Petri nets are powerful and versatile tools for modeling, simulating, analyzing and designing of complex workflow systems. This work mainly discusses a hybrid approach using neural network and Petri nets in the formal model of intelligent workflow for interorganizational cooperation. The model is called intelligent neural extended Petri nets (INEPN). INEPN not 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 on INEPN, an intelligent WfMS is developed for interorganizational cooperation in manufacturing industry. The INEPN model is an innovative method for intelligent workflow.

Published in:

Computer Supported Cooperative Work in Design, 2004. Proceedings. The 8th International Conference on  (Volume:2 )

Date of Conference:

26-28 May 2004