Please use this identifier to cite or link to this item:
https://scidar.kg.ac.rs/handle/123456789/11931
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.rights.license | restrictedAccess | - |
dc.contributor.author | Blagojević, Marija | - |
dc.contributor.author | Radović M. | - |
dc.contributor.author | Radović, Maja | - |
dc.contributor.author | Filipovic, Nenad | - |
dc.date.accessioned | 2021-04-20T19:35:34Z | - |
dc.date.available | 2021-04-20T19:35:34Z | - |
dc.date.issued | 2015 | - |
dc.identifier.uri | https://scidar.kg.ac.rs/handle/123456789/11931 | - |
dc.description.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. | - |
dc.rights | info:eu-repo/semantics/restrictedAccess | - |
dc.rights | info:eu-repo/semantics/restrictedAccess | - |
dc.source | 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015 | - |
dc.title | Neural network based approach for predicting maximal wall shear stress in the artery | - |
dc.type | conferenceObject | - |
dc.identifier.doi | 10.1109/BIBE.2015.7367713 | - |
dc.identifier.scopus | 2-s2.0-84962890423 | - |
Appears in Collections: | Faculty of Engineering, Kragujevac Faculty of Technical Sciences, Čačak |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
PaperMissing.pdf Restricted Access | 29.86 kB | Adobe PDF | View/Open |
Items in SCIDAR are protected by copyright, with all rights reserved, unless otherwise indicated.