Reliability study of generalized exponential distribution based on inverse power law using artificial neural network with Bayesian regularization

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dc.contributor.authorSindhu, Tabassum Naz
dc.contributor.authorÇolak, Andaç Batur
dc.contributor.authorLone, Showkat Ahmad
dc.contributor.authorShafiq, Anum
dc.date.accessioned2023-06-23T10:30:53Z
dc.date.available2023-06-23T10:30:53Z
dc.date.issued2023en_US
dc.departmentRektörlük, Bilişim Teknolojileri Uygulama ve Araştırma Merkezien_US
dc.description.abstractThe investigation of lifetime reliability analysis is vital for confirming the quality of devices, equipment, electronic tube flops, and so forth. Statistical investigators have become more interested in lifetime model exploration in recent years, particularly in the last decade, without considering the issue of modeling the metrics of model reliability using artificial neural networks (ANNs). This study addresses this vacuum by discussing the multilayer ANN with Bayesian regularization modeling for reliability metrics of generalized exponential model based on inverse power law (IPL). The numerical findings of the reliability investigations and the values obtained from the ANN have been examined and analyzed carefully. The findings show that ANNs are a powerful and useful mathematical tool for analyzing the reliability of lifetime model based on IPL. Finally, a real life framework is implemented that support the theory of a research study.en_US
dc.identifier.doi10.1002/qre.3352en_US
dc.identifier.scopus2-s2.0-85152957193en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11467/6670
dc.identifier.urihttps://doi.org/10.1002/qre.3352
dc.identifier.wosWOS:000972508300001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Ltden_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.subjectartificial neural network; mean inactivity time; mean residual life; mean time to failure; reliability functionen_US
dc.titleReliability study of generalized exponential distribution based on inverse power law using artificial neural network with Bayesian regularizationen_US
dc.typeArticleen_US

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