DocumentCode
3150033
Title
A knowledge acquisition approach for multi-autonomic objects flexible workflow
Author
Wang, Dongbo ; Yan, Xiutian ; Chen, Bing ; Fan, Yangxi
Author_Institution
Sch. of Mechatron., Northwestern Polytech. Univ., Xi´´an, China
fYear
2009
fDate
6-9 July 2009
Firstpage
1385
Lastpage
1389
Abstract
The multi-autonomic objects flexible workflow is a flexible workflow with Autonomic Objects (AO) embedded in workflow activities, AO can improve the intelligence of flexible workflow by using of autonomic computing technology. In order to benefit the autonomic computing of AO, a knowledge acquisition approach based on rough set is proposed to acquire knowledge in flexible workflow instance. The AO and multi-autonomic objects flexible is introduced at first, then the AO knowledge acquisition architecture is designed and application of rough set is investigated, and a AO inference learning approach based on rough set is studied further to improve the known knowledge, finally the knowledge acquisition approach in demonstrated in a multi-autonomic objects flexible workflow and the results shows that this approach can acquire knowledge satisfactorily.
Keywords
inference mechanisms; knowledge acquisition; learning (artificial intelligence); rough set theory; autonomic computing technology; inference learning; knowledge acquisition; multiautonomic objects flexible workflow; rough set; Automation; Collaborative work; Computer architecture; Expert systems; Intelligent agent; Knowledge acquisition; Mechatronics; Process design; Product development; Supply chain management; Autonomic Computing; Flexible Workflow; Knowledge Acquisition; Rough set;
fLanguage
English
Publisher
ieee
Conference_Titel
Computers & Industrial Engineering, 2009. CIE 2009. International Conference on
Conference_Location
Troyes
Print_ISBN
978-1-4244-4135-8
Electronic_ISBN
978-1-4244-4136-5
Type
conf
DOI
10.1109/ICCIE.2009.5223484
Filename
5223484
Link To Document