计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (16): 221-225.

• 工程与应用 • 上一篇    下一篇

求解药代动力学参数的自适应混合粒子群算法

欧阳艾嘉1,刘利斌2,乐光学1,3,李肯立3   

  1. 1.嘉兴学院 数理与信息工程学院,浙江 嘉兴 314001
    2.池州学院 数学与计算机科学系,安徽 池州 247000
    3.湖南大学 计算机与通信学院,长沙 410082
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-06-01 发布日期:2011-06-01

Adaptive hybrid particle swarm optimization for solving parameters of pharmacokinetics

OUYANG Aijia1,LIU Libin2,YUE Guangxue1,3,LI Kenli3   

  1. 1.College of Mathematics and Information Engineering, Jiaxing University,Jiaxing,Zhejiang 314001,China
    2.Department of Mathematics and Computer Science,University of Chizhou,Chizhou,Anhui 247000,China
    3.School of Computer and Communication, Hunan University,Changsha 410082,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-06-01 Published:2011-06-01

摘要: 针对传统方法具有初始值敏感和进化算法无法确定搜索范围等缺陷,将Nelder-Mead单纯形与粒子群算法相结合,提出了一种基于Nelder-Mead单纯形与粒子群算法的具有时变加速因子的自适应混合粒子群算法。将该混合算法用于血管外给药二室模型参数优化的实验之中。仿真实验结果表明,算法计算精度高而且鲁棒性强,是一种新颖的解决药代动力学参数优化的较好方法。

关键词: 药代动力学, 粒子群算法, Nelder-Mead单纯形, 二室模型, 参数优化

Abstract: Traditional method is sensitive to initial values and evolutionary search algorithm can not determine the scope of search on the parameters optimization of pharmacokinetics,the paper combines Particle Swarm Optimization(PSO) with Nelder-Mead Simplex Method(NM-SM),proposes a Adaptive Hybrid PSO(AHPSO) with Time-Varying Acceleration Coefficients(TVAC).The hybrid algorithm is applied to optimize the parameters of two-compartment model with extravascular administration.The simulation results show that AHPSO is a novel and good algorithm with high accuracy and strong robustness for parameters optimization of pharmacokinetics.

Key words: pharmacokinetics, particle swarm optimization, Nelder-Mead simplex method, two-compartment model, parameter optimization