基于改进布谷鸟搜索算法的威布尔混合参数估计

Kuo Chi, Jianshe Kang, Guangbiao Wang, Ruifeng Yang
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引用次数: 1

摘要

针对Weibull混合物参数难以准确估计的问题,提出了一种基于改进布谷鸟搜索算法(CSA)的Weibull混合物参数估计新方法。基于残差平方和(RSS)最小的思想,建立了优化模型,并用改进的CSA进行求解。算法改进方案包括改进发现概率方案、改进步长尺度方案及其综合方案。在案例研究中,以工艺挡风玻璃为对象,采用双重威布尔混合作为拟合函数。分别采用基于CSA的4种参数估计方法和3种改进CSA的参数估计方法进行了2000次参数估计。结果表明,基于CSA综合方案的方法精度得到了提高,且综合方案优于其他三种算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter estimation of weibull mixtures based on improved cuckoo search algorithm
As to the problem that it is difficult to estimate the parameters of Weibull mixtures accurately, a new parameter estimation method for Weibull mixtures based on the improved cuckoo search algorithm (CSA) is proposed. The optimization model, which is solved by the improved CSA, is established based on the idea of minimizing the residual sum of squares (RSS). The algorithmic improvement has three schemes including the improvement of discovering probability, the improvement of step-size scale and their integrated scheme. In the case study, craft windshields are regarded as the objects, and two-fold Weibull mixture is considered as the fitting function. Four parameter estimation methods based on CSA and three improved CSAs are respectively used to estimate the parameters for 2000 times. The results are compared and the result proves that the accuracy of the method based on the integrated scheme of CSA is improved by the integrated scheme is better than other three algorithms.
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