[1]彭珍瑞,赵宇,殷红,等.基于Memetic算法的桥梁传感器优化布置[J].智能系统学报,2014,9(06):685-689.[doi:10.3969/j.issn.1673-4785.201309018]
 PENG Zhenrui,ZHAO Yu,YIN Hong,et al.Optimal sensor placement of a bridge based on memetic algorithm[J].CAAI Transactions on Intelligent Systems,2014,9(06):685-689.[doi:10.3969/j.issn.1673-4785.201309018]
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基于Memetic算法的桥梁传感器优化布置
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年06期
页码:
685-689
栏目:
出版日期:
2014-12-25

文章信息/Info

Title:
Optimal sensor placement of a bridge based on memetic algorithm
作者:
彭珍瑞1 赵宇1 殷红1 彭宝瑞2
1. 兰州交通大学 机电工程学院, 甘肃 兰州 730070;
2. 兰州大学 土木工程与力学学院, 甘肃 兰州 730000
Author(s):
PENG Zhenrui1 ZHAO Yu1 YIN Hong1 PENG Baorui2
1. School of Mechatronics Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China;
2. School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, China
关键词:
桥梁传感器优化布置Memetic算法遗传算法模拟退火算法
Keywords:
bridgeoptimal sensor placementmemetic algorithmgenetic algorithmsimulated annealing algorithm
分类号:
TP18
DOI:
10.3969/j.issn.1673-4785.201309018
文献标志码:
A
摘要:
针对桥梁传感器优化布置问题,提出了一种基于Memetic算法的传感器优化布置方法。首先将传感器优化布置问题转化为最优化问题,建立其数学模型,并运用Memetic优化算法求解传感器最优化布置。该算法将遗传算法的全局搜索与模拟退火算法的局部搜索相结合,克服了遗传算法易早熟和陷入局部最优等问题。某悬索桥算例表明,该算法可以解决桥梁传感器优化布置问题,且与遗传算法对比,Memetic算法显示出较好的收敛速度及寻优能力。
Abstract:
In this paper, an optimal sensor placement algorithm based on the memetic algorithm is proposed to solve the problem of optimal sensor placement of a bridge. Firstly the optimal sensor placement is transformed into an optimization problem. Next, the mathematic model is established and the memetic algorithm is used to solve the problem. The memetic algorithm combines global search of the genetic algorithm with local search of the simulated annealing algorithm to overcome the premature convergence problem and local best solution in genetic algorithm. This algorithm was applied in the optimal sensor placement of a suspension bridge. The results indicated that the memetic algorithm can be used to solve the problem, showing better optimization performance and faster convergence speed in comparison with the genetic algorithm.

参考文献/References:

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相似文献/References:

[1]董小圆,彭珍瑞,殷红,等.传感器优化布置的距离系数-Fisher信息准则[J].智能系统学报,2017,12(01):32.[doi:10.11992/tis.201604026]
 DONG Xiaoyuan,PENG Zhenrui,YIN Hong,et al.Distance coefficient-Fisher information criterion for optimal sensor placement[J].CAAI Transactions on Intelligent Systems,2017,12(06):32.[doi:10.11992/tis.201604026]

备注/Memo

备注/Memo:
收稿日期:2013-9-6;改回日期:。
基金项目:国家自然科学基金资助项目(61463028);甘肃省高等学校基本科研业务费资助项目(213054);甘肃省教育厅科研资助项目(2013027).
作者简介:彭珍瑞,男,1972年生,教授,博士,主要研究方向为智能优化、测控技术。主持国家自然科学基金项目1项、甘肃省自然科学基金2项、陇原青年创新人才扶持计划项目1项和甘肃省教育厅项目1项,发表学术论文30余篇,获得实用新型专利2项;赵宇,女,1990年生,助教,主要研究方向智能优化、检测技术。发表学术论文3篇。
通讯作者:彭珍瑞.E-mail:pzrui@163.com.
更新日期/Last Update: 2015-06-16