Estimating the parameters of twofold Weibull mixture model in right-censored reliability data by using genetic algorithm

Tekeli E., Yüksel G.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.51, sa.11, ss.6621-6634, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 51 Sayı: 11
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1080/03610918.2020.1808681
  • Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Computer & Applied Sciences, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.6621-6634
  • Anahtar Kelimeler: Genetic algorithm, Mixture distribution, Reliability, Twofold Weibull, SYSTEM LIFETIME DATA, INFERENCE, OPTIMIZATION
  • Çukurova Üniversitesi Adresli: Evet

Özet

In this article, a new method was practiced to form a model by using twofold Weibull mixture distribution in right-censored reliability data. The method depends on estimating the parameters of right-censored twofold Weibull mixture distribution in a most appropriate way to the data by using genetic algorithm techniques. The best model was tried to be found by using MSE, MAE and MAPE metrics, respectively, as fitness function in the method. To test the model, failure data of aircraft planes' windshield, which is often used in the literature, was used and the results were compared with other methods in the literature. Furthermore, the performance of the method was compared for the sample sizes, censorship ratios and mixture proportions by conducting Monte Carlo simulation study.