نمایش مختصر رکورد

dc.contributor.authorMajidnezhad, V.en_US
dc.date.accessioned1399-07-09T06:04:04Zfa_IR
dc.date.accessioned2020-09-30T06:04:04Z
dc.date.available1399-07-09T06:04:04Zfa_IR
dc.date.available2020-09-30T06:04:04Z
dc.date.issued2014-07-01en_US
dc.date.issued1393-04-10fa_IR
dc.date.submitted2014-07-18en_US
dc.date.submitted1393-04-27fa_IR
dc.identifier.citationMajidnezhad, V.. (2014). A novel hybrid method for vocal fold pathology diagnosis based on russian language. Journal of AI and Data Mining, 2(2), 141-147. doi: 10.22044/jadm.2014.332en_US
dc.identifier.issn2322-5211
dc.identifier.issn2322-4444
dc.identifier.urihttps://dx.doi.org/10.22044/jadm.2014.332
dc.identifier.urihttp://jad.shahroodut.ac.ir/article_332.html
dc.identifier.urihttps://iranjournals.nlai.ir/handle/123456789/294816
dc.description.abstractIn this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. Then, for optimizing the initial feature vector, a genetic algorithm is proposed. Some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and K-nearest neighbours) and the different feature vectors (the initial and the optimized ones). Finally, a hybrid of the ensemble of decision tree and the genetic algorithm is proposed for vocal fold pathology diagnosis based on Russian Language. The experimental results show a better performance (the higher classification accuracy and the lower response time) of the proposed method in comparison with the others. While the usage of pure decision tree leads to the classification accuracy of 85.4% for vocal fold pathology diagnosis based on Russian language, the proposed method leads to the 8.5% improvement (the accuracy of 93.9%).en_US
dc.format.extent633
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoen_US
dc.publisherShahrood University of Technologyen_US
dc.relation.ispartofJournal of AI and Data Miningen_US
dc.relation.isversionofhttps://dx.doi.org/10.22044/jadm.2014.332
dc.subjectEnsemble of Decision Treeen_US
dc.subjectGenetic Algorithm (GA)en_US
dc.subjectMel Frequency Cepstral Coefficients (MFCC)en_US
dc.subjectWavelet Packet Decomposition (WPD)en_US
dc.subjectVocal Fold Pathology Diagnosisen_US
dc.subjectH.3.15.3. Evolutionary computing and genetic algorithmsen_US
dc.titleA novel hybrid method for vocal fold pathology diagnosis based on russian languageen_US
dc.typeTexten_US
dc.typeResearch/Original/Regular Articleen_US
dc.contributor.departmentUnited Institute of Informatics Problems, National Academy of Science of Belarusen_US
dc.citation.volume2
dc.citation.issue2
dc.citation.spage141
dc.citation.epage147


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