Search from over 60,000 research works

Advanced Search

Knowledge-elicitation and data-mining: fusing human and industrial plant information

Full text not archived in this repository.
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Browne, W., Yao, L., Postlethwaite, I., Lowes, S. and Mar, M. (2006) Knowledge-elicitation and data-mining: fusing human and industrial plant information. Engineering Applications of Artificial Intelligence, 19 (3). pp. 345-359. ISSN 0952-1976 doi: 10.1016/j.engappai.2005.09.005

Abstract/Summary

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process. (C) 2005 Elsevier Ltd. All rights reserved.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/15156
Item Type Article
Refereed Yes
Divisions Science
Uncontrolled Keywords fusing data-mining methods, metal rolling
Download/View statistics View download statistics for this item

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar