dc.contributor.author | Aktepe, Adnan | |
dc.contributor.author | Ersoz, Suleyman | |
dc.contributor.author | Luy, Murat | |
dc.date.accessioned | 2020-06-25T18:06:43Z | |
dc.date.available | 2020-06-25T18:06:43Z | |
dc.date.issued | 2012 | |
dc.identifier.citation | closedAccess | en_US |
dc.identifier.isbn | 978-3-642-32908-1 | |
dc.identifier.issn | 1865-0929 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12587/5331 | |
dc.description | 13th International Conference on Engineering Applications of Neural Networks -- SEP 20-23, 2012 -- Coventry Univ, Otaniemi, FINLAND | en_US |
dc.description | LUY, Murat/0000-0002-2378-0009; Aktepe, Adnan/0000-0002-3340-244X | en_US |
dc.description | WOS: 000312463700018 | en_US |
dc.description.abstract | The aim of this study is to develop predictive Artificial Neural Network (ANN) models for welding process control of a strategic product (155 mm. artillery ammunition) in armed forces' inventories. The critical process about the production of product is the welding process. In this process, a rotating band is welded to the body of ammunition. This is a multi-input, multi-output process. In order to tackle problems in the welding process 2 different ANN models have been developed in this study. Model 1 is a Backpropagation Neural Network (BPNN) application used for classification of defective and defect-free products. Model 2 is a reverse BPNN application used for predicting input parameters given output values. In addition, with the help of models developed mean values of best values of some input parameters are found for a defect-free weld operation. | en_US |
dc.description.sponsorship | Industry Thesis Program of Ministry of Science, Industry and Technology of Turkey [00748.STZ.2010-2] | en_US |
dc.description.sponsorship | This study is supported by a grant from Industry Thesis Program of Ministry of Science, Industry and Technology of Turkey (Grant No:00748.STZ.2010-2). | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer-Verlag Berlin | en_US |
dc.relation.ispartofseries | Communications in Computer and Information Science | |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Backpropagation neural networks | en_US |
dc.subject | welding process control | en_US |
dc.subject | artillery ammunition | en_US |
dc.title | Backpropagation Neural Network Applications for a Welding Process Control Problem | en_US |
dc.type | conferenceObject | en_US |
dc.contributor.department | Kırıkkale Üniversitesi | en_US |
dc.identifier.volume | 311 | en_US |
dc.identifier.startpage | 172 | en_US |
dc.identifier.endpage | + | en_US |
dc.relation.journal | Engineering Applications Of Neural Networks | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |