Adaptive numerical modelling of commercial aluminium plate performance

Christensen, S., Kandola, J.S., Femminella, O., Gunn, S.R., Reed, P.A.S. and Sinclair, I. (2000) Adaptive numerical modelling of commercial aluminium plate performance. In, Starke, Jr., E.A., Sanders, T.H. and Cassada, W.A. (eds.) Aluminium Alloys: Their Physical and Mechanical Properties. 7th International Conference ICAA7 Switzerland, Trans Tech, 533-538. (Materials Science Forum 331-337).


Full text not available from this repository.


Adaptive numerical methods, such as neural networks, have received considerable attention in recent years in relation to the modelling of complex physical systems. In this work a variety of such methods have been applied to the modelling/data mining of commercial materials production data, thereby avoiding the scale-up problems associated with laboratory scale investigations of materials behaviour. It is shown that adaptive numerical methods may determine valuable empirical models from such complex databases, whilst the value of transparent modelling methods (where the underlying relationships between input variables and modelled characteristics may be clearly visualised) is highlighted in providing model confidence and the potential to extract novel physical understanding.

Item Type: Book Section
Additional Information: Series ISSN 0255-5476
ISBNs: 0878498532 (hardback)
ISSNs: 0255-5476 (print)
Related URLs:
Keywords: adaptive numeric methods, data mining; empirical modelling, fuzzy logic, neural networks, support vector machines
Subjects: T Technology > TN Mining engineering. Metallurgy
Q Science > QA Mathematics
Divisions : University Structure - Pre August 2011 > School of Engineering Sciences > Engineering Materials & Surface Engineering
ePrint ID: 43065
Accepted Date and Publication Date:
Date Deposited: 10 Jan 2007
Last Modified: 31 Mar 2016 12:16

Actions (login required)

View Item View Item