吉林大学学报(理学版) ›› 2019, Vol. 57 ›› Issue (3): 517-522.

• 数学 • 上一篇    下一篇

基于Bayes微分进化算法的热源识别反问题

尹伟石, 李嘉琦   

  1. 长春理工大学 理学院, 长春 130022
  • 收稿日期:2018-07-13 出版日期:2019-05-26 发布日期:2019-05-20
  • 通讯作者: 尹伟石 E-mail:yinweishi@foxmail.com

Inverse Problem of Heat Source Identification Based onBayesianDifferential Evolution Algorithm#br#

YIN Weishi, LI Jiaqi   

  1. College of Science, Changchun University of Science and Technology, Changchun 130022, China
  • Received:2018-07-13 Online:2019-05-26 Published:2019-05-20
  • Contact: YIN Weishi E-mail:yinweishi@foxmail.com

摘要: 利用Bayes微分进化算法, 讨论二维热传导方程问题, 通过一个观测点的不同时刻观测温度, 给出热源位置的反演估计. 数值实验结果表明: 随着迭代次数的增加,  热源位置参数误差变小; 当迭代次数大于120次时, 参数反演的相对误差均控制在2%以内; 当对观测数据分别添加5%和10%的白噪声时, 相对误差变化不大, 表明算法稳定性较好.

关键词: 反问题, Bayes理论, 微分进化算法, 热源估计

Abstract: Using the Bayesiandifferential evolution algorithm, we discussed the twodimensional heat conduction equation. The inversion estimation of the heat source position was given through the observation temperature at different time of an observation point. The numerical experiment results show that, with the increase of the number of iterations, the error of the position parameter of the heat source decreases. When the number of iterations reaches 120, the relative error of the parameter inversion is controlled within 2%. When 5% and 10% white noise are added to the observed data, the relative error changes little, which indicates that the algorithm has good stability.

Key words: inverse problem, Bayesian theory, differential evolution algorithm, heat source estimation

中图分类号: 

  • O212.8