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化工学报  2015 

自适应混合粒子群约束优化算法及其在软测量模型参数估计中的应用

DOI: 10.11949/j.issn.0438-1157.20141471, PP. 222-227

Keywords: 软测量,参数估计,约束优化,粒子群,自适应

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Abstract:

对于软测量模型参数估计问题,针对传统梯度法求解非线性最小二乘模型时依赖初值、需要追加趋势分析进行验证和无法直接求解复杂问题的缺陷,提出将参数估计化为约束优化问题,使用混合优化算法求解的新思路。为此提出一种自适应混合粒子群约束优化算法(AHPSO-C)。在AHPSO-C算法中,为平衡全局搜索(混沌粒子群)和局部搜索(内点法),引入自适应内点法最大函数评价次数更新策略。对12个经典测试函数的仿真结果表明,AHPSO-C是求解约束优化问题的一种有效算法。将算法用于淤浆法高密度聚乙烯(HDPE)串级反应过程中熔融指数软测量模型参数估计,验证了方法的可行性与优越性。

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