生长曲线参数估计的改进微粒群算法

doi:10.3696/j.issn.1672-6952.2010.04.024

辽宁石油化工大学学报 ›› 2010, Vol. 30 ›› Issue (4): 88-90.DOI: 10.3696/j.issn.1672-6952.2010.04.024

生长曲线参数估计的改进微粒群算法

刘国志1, 何鹏清2

1.辽宁石油化工大学理学院，辽宁抚顺 113001; 2.辽宁抚顺供电公司,辽宁抚顺 113008

收稿日期:2010-07-01 出版日期:2010-12-20 发布日期:2017-07-17

Improved Particle Swarm Optimization Method for Estimating the Parameters of Logistic Curve

LIU Guo-zhi1, HE Peng-qing2

1.School of Sciences, Liaoning Shihua University，Fushun Liaoning 113001，P.R.China; 2.Liaoning Fushun Power Supply Company, Fushun Liaoning 113008, P.R.China

Received:2010-07-01 Published:2010-12-20 Online:2017-07-17

摘要/Abstract

摘要： 在现有文献研究的基础上，对生长曲线参数估计问题作了进一步的研究，给出了生长曲线参数估计的一个新方法—改进的微粒群最优化方法。该算法不需要计算梯度，容易应用于实际问题中。通过对微粒群算法的修正，使改进算法具有更加精确和快速的收敛性。实例计算表明，这种参数估计发具有较高的精度。

关键词: 生长曲线, 参数估计, 微粒群最优化

Abstract: It makes further research on estimating the parameters of logistic curve on based of the present document, and an improved method for estimating the parameters of logistic curve-improved particle swarm optimization method was presented. It does not require gradient computation, and intends to produce faster and more accurate convergence. The sampling calculation shows that parameter estimation method is higher precise.

Key words: Logistic curve, Parameter estimation, Particle swarm optimization

刘国志, 何鹏清. 生长曲线参数估计的改进微粒群算法[J]. 辽宁石油化工大学学报, 2010, 30(4): 88-90.

LIU Guo-zhi, HE Peng-qing. Improved Particle Swarm Optimization Method for Estimating the Parameters of Logistic Curve[J]. Journal of Liaoning Petrochemical University, 2010, 30(4): 88-90.

生长曲线参数估计的改进微粒群算法

Improved Particle Swarm Optimization Method for Estimating the Parameters of Logistic Curve

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