Weibull Parameter Estimation Using Particle Swarm Optimization Algorithm

  • Authors

    • Ekene Gabriel Okafor
    • Okechukwu Emmanuel Ezugwu
    • Paul Olugbeji Jemitola
    • Youchao Sun
    • Zhong Lu
    2018-08-26
    https://doi.org/10.14419/ijet.v7i3.32.18380
  • Algorithm, Parameter estimation, Particle Swarm Optimization, Reliability, Weibull distribution

  • Abstract

    Many research works on Weibull parameter estimation has focused on graphical or analytical techniques, with little effort devoted towards the use of population based optimization algorithm. Accurate estimation of failure distributive parameter such as Weibull is a key requirement for efficient reliability analysis. In this study Particle Swarm Optimization Algorithm (PSOA), with particle position and velocity iteratively updated was used to estimate Weibull parameters. Probability density function and reliability plots were generated using the results obtained. Generally, PSOA shows better parameter estimation in comparison with analytical method based on Maximum Likelihood Estimator (MLE).

     

     

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  • How to Cite

    Gabriel Okafor, E., Emmanuel Ezugwu, O., Olugbeji Jemitola, P., Sun, Y., & Lu, Z. (2018). Weibull Parameter Estimation Using Particle Swarm Optimization Algorithm. International Journal of Engineering & Technology, 7(3.32), 7-10. https://doi.org/10.14419/ijet.v7i3.32.18380

    Received date: 2018-08-28

    Accepted date: 2018-08-28

    Published date: 2018-08-26