[1]张煜东,吴乐南,韦耿,等.用于多指数拟合的一种混沌免疫粒子群优化[J].东南大学学报(自然科学版),2009,39(4):678-683.[doi:10.3969/j.issn.1001-0505.2009.04.006]
 Zhang Yudong,Wu Lenan,Wei Geng,et al.Chaotic immune particle swarm optimization for multi-exponential fitting[J].Journal of Southeast University (Natural Science Edition),2009,39(4):678-683.[doi:10.3969/j.issn.1001-0505.2009.04.006]
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用于多指数拟合的一种混沌免疫粒子群优化()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
39
期数:
2009年第4期
页码:
678-683
栏目:
信息与通信工程
出版日期:
2009-07-20

文章信息/Info

Title:
Chaotic immune particle swarm optimization for multi-exponential fitting
作者:
张煜东 吴乐南 韦耿 颜俊 朱庆
东南大学信息科学与工程学院,南京 210096
Author(s):
Zhang Yudong Wu Lenan Wei Geng Yan Jun Zhu Qing
School of Information Science and Engineering,Southeast University,Nanjing 210096,China
关键词:
多指数拟合 迭代最小平方法 粒子群优化 混沌算子 人工免疫系统
Keywords:
multi-exponential fitting iterative least square particle swarm optimization chaotic operator artificial immune system
分类号:
TN911.73
DOI:
10.3969/j.issn.1001-0505.2009.04.006
摘要:
为了更好地逼近真实物理场景,对传统的多指数模型作了一些改进,将权因子设置为噪声方差平方的倒数,提出一种基于循环矩阵(CM)的算法用于估计衰减项数.为了求解上述改进模型,提出一种混沌免疫粒子群优化(CIPSO)算法.该算法将人工免疫系统中的克隆、交叉、变异和接收器修正算法嵌入粒子群算法中,并采用混沌算子实现变异,然后将惯性因子改为自适应变化.实验表明:提出的权因子设置更符合实际; 用于估计项数的CM算法在估计精度与运行时间上均优于传统的ILS算法; CIPSO算法在收敛精度与运行时间上也优于传统的优化算法,如可信域法、LM法、高斯-牛顿法、差分进化算法和粒子群算法等.
Abstract:
In order to approach practical physical scene,traditional multi-exponential model is improved as follows: the weight factor is set as the reciprocal of the square of noise variance, and a method based on circular matrix(CM)is proposed to estimate the number of decay terms. To efficiently solve this model, a novel algorithm called chaotic immune particle swarm optimization(CIPSO)is proposed. The operators of clone, crossover, mutation, and receptor editing are embedded into particle swarm optimization; the chaotic operator is used to realize mutation, and the inertial factor is stipulated as adaptive variation. Experiments demonstrate that the proposed setting of weight factor is more practical; the CM method is superior to traditional iterative least square(ILS)method in terms of estimation accuracy and computation time; the CIPSO algorithm outperforms traditional optimization methods such as the trust-region method, Levenberg-Marquardt(LM)method, Gaussian-Newton method, difference evolution algorithm, PSO algorithm in terms of convergence accuracy and computation time.

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备注/Memo

备注/Memo:
作者简介: 张煜东(1985—),男,博士生; 吴乐南(联系人),男,博士,教授,博士生导师,wuln@seu.edu.cn.
基金项目: 国家自然科学基金资助项目(60872075)、高等学校科技创新工程重大项目培育基金资助项目(706028)、江苏省自然科学基金资助项目(BK2007103).
引文格式: 张煜东,吴乐南,韦耿,等.用于多指数拟合的一种混沌免疫粒子群优化[J].东南大学学报:自然科学版,2009,39(4):678-683.[doi:10.3969/j.issn.1001-0505.2009.04.006]
更新日期/Last Update: 2009-07-20