Dynamic aerodynamic parameter estimation using a dynamic particle swarm optimization algorithm for rolling airframes

2020 ◽  
Vol 42 (11) ◽  
Author(s):  
Ayham Mohamad ◽  
Jalal Karimi ◽  
Alireza Naderi
Keyword(s):  
Parameter Estimation ◽  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Aerodynamic Parameter ◽  
Swarm Optimization

scholarly journals Weibull Parameter Estimation Using Particle Swarm Optimization Algorithm

2018 ◽  
Vol 7 (3.32) ◽  
pp. 7
Author(s):  
Ekene Gabriel Okafor ◽  
Okechukwu Emmanuel Ezugwu ◽  
Paul Olugbeji Jemitola ◽  
Youchao Sun ◽  
Zhong Lu
Keyword(s):  
Parameter Estimation ◽  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Analytical Techniques ◽  
Population Based ◽  
Accurate Estimation ◽  
Weibull Parameter ◽  
Swarm Optimization

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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