ANFIS and regression-based ANOVA for attribute and variable prediction: a case of quality characteristics in the cement bags industry Online publication date: Fri, 14-Jul-2023
by Mahmoud A. El-Sharief; Omar Salah; Mahmoud Heshmat
International Journal of Industrial and Systems Engineering (IJISE), Vol. 44, No. 3, 2023
Abstract: Efficient models are significant to manufacturing systems for the purpose of prediction and performance evaluation. Traditionally, regression models have been widely held for this purpose; recently, soft computing models are widely used. Efficiency of soft computing models depends on the size of the problem dataset. In this paper, we conduct a regression-based ANOVA study and ANFIS for cement bags production. Quality characteristics of bag dimensions are considered. The results show that ANFIS can predict attributes and variables of production lines more than regression-based ANOVA.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Industrial and Systems Engineering (IJISE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com