Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/3809
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dc.contributor.authorDamirchi-Darasi, S. Rahimi-
dc.contributor.authorZarandi, Mohammad Hossein Fazel-
dc.contributor.authorTürksen, İsmail Burhan-
dc.contributor.authorİzadi, M.-
dc.date.accessioned2020-09-18T06:43:05Z-
dc.date.available2020-09-18T06:43:05Z-
dc.date.issued2019-01
dc.identifier.citationDamirchi-Darasi, S. R., Zarandi, M. F., Turksen, I. B., & Izadi, M. (2019). Type-2 fuzzy rule-based expert system for diagnosis of spinal cord disorders. Scientia Iranica. Transaction E, Industrial Engineering, 26(1), 455-471.en_US
dc.identifier.issn1026-3098
dc.identifier.urihttps://hdl.handle.net/20.500.11851/3809-
dc.identifier.urihttp://scientiairanica.sharif.edu/article_20228.html-
dc.description.abstractThe majority of people have experienced pain in their low back or neck in their lives. In this paper, a type-2 fuzzy rule-based expert system is presented for diagnosing the spinal cord disorders. The interval type-2 fuzzy logic system permits us to handle the high uncertainty of diagnosing the type of disorder and its severity. The spinal cord disorders are studied in five categories using historical data and clinical symptoms of the patients. The main novelty of this paper lies in presentation of the interval type-2 fuzzy hybrid rule-based system, which is a combination of the forward and backward chaining approaches in its inference engine and avoids unnecessary medical questions. Use of parametric operations for fuzzy calculations increases the robustness of the system and the compatibility of the diagnosis with a wide range of physicians' diagnosis. The outputs of the system are comprised of type of disorder, location, and severity as well as the necessity of taking an M.R. Image. A comparison of the performance of the developed system with the expert shows an acceptable accuracy of the system in diagnosing the disorders and determining the necessity of the M.R. Image.en_US
dc.language.isoenen_US
dc.publisherSharif University of Technologyen_US
dc.relation.ispartofScientia Iranicaen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectType-2 fuzzy expert systemen_US
dc.subjectForward-backward chainingen_US
dc.subjectParameter optimizationen_US
dc.subjectSpinal cord disorderen_US
dc.subjectRule-based expert systemen_US
dc.titleType-2 Fuzzy Rule-Based Expert System for Diagnosis of Spinal Cord Disordersen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.identifier.volume26
dc.identifier.issue1
dc.identifier.startpage455
dc.identifier.endpage471
dc.authorid0000-0001-6444-7301-
dc.identifier.wosWOS:000459061300001en_US
dc.identifier.scopus2-s2.0-85062528325en_US
dc.institutionauthorTürkşen, İsmail Burhan-
dc.identifier.doi10.24200/sci.2018.20228-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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