A Comparison of Artificial Neural Networks and Multiple Linear Regression Models As Predictors of Discard Rates In Plastic Injection Molding

Vesile Sinem Arıkan Kargı

Alphanumeric Journal, 2015, vol. 3, issue 2, 65-72

Abstract: In today’s global competitive environment, it is important to be able to evaluate the efficient use of a firms’ resources. The aim of this study is to predict the discard rate for headlight frames before the project of an automotive sub-industry firm in Bursa. For this prediction, the multilayer perceptron model, the radial basis function network model and multiple linear regression models were used. Matlab R2010b software was used for the multilayer perceptron model and radial basis function network solutions, and SPSS 13 packet software was used to solve the multiple linear regressions. Comparing the three models, the multilayer perceptron model was identified as the best predictive model.

Keywords: Artificial Neural Networks; Discard Rate; Multilayer Perceptron Model; Multiple Linear Regression Model; Radial Basis Function Network Model (search for similar items in EconPapers)
JEL-codes: C13 C45 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.alphanumericjournal.com/media/Issue/vo ... ple-line_UUMy5lK.pdf (application/pdf)
https://alphanumericjournal.com/article/a-comparis ... c-injection-molding/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:anm:alpnmr:v:3:y:2015:i:2:p:65-72

DOI: 10.17093/aj.2015.3.2.5000149667

Access Statistics for this article

More articles in Alphanumeric Journal from Bahadir Fatih Yildirim
Bibliographic data for series maintained by Bahadir Fatih Yildirim ().