A comparative analysis of maximum likelihood estimation and artificial neural network modeling to assess electrical component reliability

Basit Öğe Kaydı
dc.contributor.authorÇolak, Andaç Batur
dc.contributor.authorSindhu, Tabassum Naz
dc.contributor.authorLone, Showkat Ahmad
dc.contributor.authorAkhtar, Md Tanwir
dc.contributor.authorShafiq, Anum
dc.date.accessioned2023-01-30T11:15:42Z
dc.date.available2023-01-30T11:15:42Z
dc.date.issued2022en_US
dc.departmentRektörlük, Bilişim Teknolojileri Uygulama ve Araştırma Merkezien_US
dc.description.abstractThis study focuses on accurately predicting the behavior of new power functiondistribution using neural network and optimizing it using maximum likelihoodestimation. The main motivation of this study is that there is no study inthe literature that optimizes and predicts the reliability analysis of lifetimemodels by combining artificial neural networks and maximum likelihoodestimation methods. The numerical findings of the reliability investigationsand the values got from maximum likelihood estimation and artificial neuralnetwork modeling have been examined and investigated carefully. For theartificial neural network models, the R value was 0.99999 and the deviationratios were lower than 0.08%. The findings reveal that artificial neural networksare a powerful and useful mathematical tool for analyzing the reliabilityof lifetime models and numerical study findings via maximum likelihoodestimation are completely in accord with artificial neural network predictionresults.en_US
dc.identifier.doi10.1002/qre.3233en_US
dc.identifier.scopus2-s2.0-85142294436en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11467/6166
dc.identifier.urihttps://doi.org/10.1002/qre.3233
dc.identifier.wosWOS:000888933400001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherJohn Wiley and Sonsen_US
dc.relation.ispartofQuality and Reliability Engineering Internationalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectmean time to failure, reliability function, maximum likelihood estimation, artificial neuralnetwork, failure rate functionen_US
dc.titleA comparative analysis of maximum likelihood estimation and artificial neural network modeling to assess electrical component reliabilityen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
Quality Reliability Eng - 2022 - olak - A comparative analysis of maximum likelihood estimation and artificial neural.pdf
Boyut:
4.32 MB
Biçim:
Adobe Portable Document Format
Açıklama:
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.56 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu