A comparison of factorial and random experimental design methods for the development of regression and neural network simulation metamodels
UNSPECIFIED. (1999) A comparison of factorial and random experimental design methods for the development of regression and neural network simulation metamodels. JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 50 (10). pp. 1018-1033. ISSN 0160-5682Full text not available from this repository.
This paper compares two forms of experimental design methods that may be used for the development of regression and neural network simulation metamodels. The experimental designs considered are full factorial design!; and random designs. The paper shows that, for two example problems, neural network metamodels using a randomised experimental design produce more accurate and efficient metamodels than those produced by similar sized factorial designs with either regression or neural networks. The metamodelling techniques are compared by their ability to predict the results from two manufacturing systems that have different levels of complexity. The results of the comparison suggest that neural network metamodels outperform conventional regression metamodels, especially when data sets based on randomised simulation experimental designs are used to produce the metamodels rather than data sets from similar sized full factorial experimental designs.
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management|
|Journal or Publication Title:||JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY|
|Official Date:||October 1999|
|Number of Pages:||16|
|Page Range:||pp. 1018-1033|
Actions (login required)
Downloads per month over past year