| dc.contributor.author | Alkim E. | |
| dc.contributor.author | Gürbüz E. | |
| dc.contributor.author | Kiliç E. | |
| dc.date.accessioned | 2020-06-21T09:36:51Z | |
| dc.date.available | 2020-06-21T09:36:51Z | |
| dc.date.issued | 2011 | |
| dc.identifier.isbn | 9.78146E+12 | |
| dc.identifier.uri | https://doi.org/10.1109/SIU.2011.5929582 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12712/4594 | |
| dc.description | 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 -- 20 April 2011 through 22 April 2011 -- Antalya -- 85528 | en_US |
| dc.description.abstract | In this study, the Learning Vector Quantization (LVQ) network model is enhanced with attaching conscience mechanism to be used in diagnosis of thyroid disorders, so that network's disease diagnostic success percentage is increased and the conscience coefficients which is used in the network is obtained in an adaptive manner. It is observed that the LVQ network model created with this new mechanism learns faster than the other networks, besides conscience mechanism increases percentage of network's performance. The results obtained are discussed by comparison with similar studies. © 2011 IEEE. | en_US |
| dc.language.iso | tur | en_US |
| dc.relation.isversionof | 10.1109/SIU.2011.5929582 | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.title | A new intelligent diagnosis method to determine thyroid disorders | en_US |
| dc.title.alternative | Ti?roi?t bozuklugu tespi?ti? i?çi?n yeni? bi?r akilli tanilama yöntemi? | en_US |
| dc.type | conferenceObject | en_US |
| dc.contributor.department | OMÜ | en_US |
| dc.identifier.startpage | 38 | en_US |
| dc.identifier.endpage | 41 | en_US |
| dc.relation.journal | 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
