基于群智能算法的三参数Weibull分布函数的参数辨识

模型的参数估计是影响模型准确性的一个重要方面。不同的参数估计方法，会使模型拟合结果相差很大，本文在对以往传统的参数估计方法进行分析评述的基础上，介绍了近年来应用广泛的四种群智能优化算法，即布谷鸟搜索算法、蚁群算法、萤火虫算法及模拟退火算法，并将其应用于三参数Weibull分布函数模型的参数辨识。通过对以上四种优化算法性能分析比较，认为在Weibull模型参数估计中，群智能优化算法是一种更为有效的方法。

The model parameter estimation is an important aspect to affect the accuracy of the model. The different estimation of the parameters will lead different results of model fitting. Based on the conventional parameter estimation methods summarized, this paper introduces the four wide range of swarm intelligence optimization algorithm used widely in recent years, the cuckoo search algorithm, ant colony algorithm, firefly algorithm and simulated annealing algorithm, respectively, to estimate the three parameters of the Weibull distribution function model. Through comparison of above four optimization algorithm, we obtained that swarm intelligence optimization algorithm is a more effective model of Weibull parameter estimation method.