Author/Authors
DELİKANLI, Kamil Süleyman Demirel Üniversitesi - Mühendislik Fakültesi - Makine Mühendisliği Bölümü, Turkey , AKSOY, Bekir Süleyman Demirel Üniversitesi - Senirkent Meslek Yüksekokulu (Senirkent MYO) - Bilgisayar Teknolojileri Programı, Turkey
Title Of Article
Predicting the Earing Using Gene Expressive Programming at Deep Drawing of Technical Aluminium AA1100
شماره ركورد
41285
Abstract
It is emphasized that, earing problem which is one of the material origin problems that occurs during deep drawing of cold rolled AA1100 aluminium sheets and effects of the heat treating parameters to take away or minimize the earing problem were investigated. In recent years, artificial intelligence methods are widely used to estimate the results. In this study, Gene Expressive Programming (GEP) is used to estimate the height of earings. Annealing temperature and annealing time are approved as input parameters; earing height is approved as output parameter. Results are estimated with the ratio of 95,89 % at the GEP environment using only four arithmetical operation variables with the help of these parameters.
From Page
30
NaturalLanguageKeyword
Deep drawing , Earing , Gen Expressive Programming
JournalTitle
Sdu Journal Of Technical Sciences
To Page
36
JournalTitle
Sdu Journal Of Technical Sciences
Link To Document