Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/11931
Title: Neural network based approach for predicting maximal wall shear stress in the artery
Authors: Blagojević, Marija
Radović M.
Radović, Maja
Filipovic, Nenad
Issue Date: 2015
Abstract: © 2015 IEEE. This paper describes the use of artificial neural networks in predicting value and position maximal wall shear stress in aneurysm. For the purpose of neural network training, back propagation algorithm was used. Input data in the network are geometric parameters of aneurysm model. Obtained results indicate the possibility of a successful application of neural networks in the problems of predicting certain parameters of arteries. Future work relates to the creation of a web-based application that allows users to display the results.
URI: https://scidar.kg.ac.rs/handle/123456789/11931
Type: conferenceObject
DOI: 10.1109/BIBE.2015.7367713
SCOPUS: 2-s2.0-84962890423
Appears in Collections:Faculty of Engineering, Kragujevac
Faculty of Technical Sciences, Čačak

Page views(s)

207

Downloads(s)

5

Files in This Item:
File Description SizeFormat 
PaperMissing.pdf
  Restricted Access
29.86 kBAdobe PDFThumbnail
View/Open


Items in SCIDAR are protected by copyright, with all rights reserved, unless otherwise indicated.