[1]蒋鼎国,张宇林,焦竹青,等.基于QPSCO算法的传感器优化配置[J].南京理工大学学报(自然科学版),2009,(04):459-463.
 JIANG Ding-guo,ZHANG Yu-lin,JIAO Zhu-qing,et al.Optimal Sensor Placement Based on QPSCO Algorithm[J].Journal of Nanjing University of Science and Technology,2009,(04):459-463.
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基于QPSCO算法的传感器优化配置
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2009年04期
页码:
459-463
栏目:
出版日期:
2009-08-30

文章信息/Info

Title:
Optimal Sensor Placement Based on QPSCO Algorithm
作者:
蒋鼎国 1 张宇林 2 焦竹青 1 徐保国 1
1.江南大学通信与控制工程学院, 江苏无锡214122; 2.淮阴工学院电子信息工程系,江苏淮安223002
Author(s):
JIANG Ding-guo1ZHANG Yu-lin2JIAO Zhu-qing1XU Bao-guo1
1.School of Communication and Control Engineering,Jiangnan University,Wuxi 214122,China;
关键词:
曲线拟合 最小二乘法 量子粒子群协同优化算法 传感器优化配置
Keywords:
curve-fitting least-square principle quantum-behaved particle swarms cooperative optimization algorithm optimal placement of sensor
分类号:
TP212
摘要:
针对以曲线拟合为目标的传感器配置问题,提出了一种基于量子粒子群协同优化(Quantum-behaved particle swarms cooperative optimization,简称QPSCO)算法的传感器优化配置方法。在QPSCO算法中,采用双层的多粒子群协同优化结构,同时引入参数变异策略,在扩大搜索范围的同时加快该算法收敛;将加权最小二乘法的误差平方和引入适应度函数中,以提高传感器位置曲线的拟合精度,从而实现传感器的优化配置。实验结果表明,该方案应用于土壤信息采集系统,不仅可以达到比粒子群优化(Particle swarm optimization,简称PSO)算法和量子粒子群优化(Quantum-behaved particle swarm optimization,简称QPSO)算法更好的寻优结果,而且具有比遗传算法更理想的位置拟合精度,是一种有效可行的传感器配置方法。
Abstract:
Focusing on the problem of the sensor placement,a scheme of optimal sensor placement based on quantum-behaved particle swarms cooperative optimization(QPSCO) algorithm is proposed.A two-layer framework with particle swarms cooperative optimization and a mutation parameter is introduced by the QPSCO algorithm for larger searching scale and quicker convergence.Moreover,the residual sum of squares in least-square principle is introduced into the fitness function to enhance the fitting precision of the sensor position curve.The optimal sensor placement is accomplished.This method of optimal sensor placement is applied into the soil information gathering system,and the test result demonstrates that this scheme,which not only brings better optimization effect than particle swarm optimization and quantum-behaved particle swarm optimization,but also has more ideal position fitting accuracy than genetic algorithm,is effective and feasible to sensor placement.

参考文献/References:

[ 1] MoonHS, Kmi YB, BeattidRJ. Mult-i sensor data fu-sion for mi provingperformanceandreliabilityof fully au-tomaticwelding system[ J]. International Journal ofAd-vanceManufactureTechnology, 2006, 28: 286-293.
[ 2] DongWen, PentlandA. Mult-i sensor data fusionusing the influencemodel [A]. Proceedings of the Interna-tionalWorkshop onWearable and Implantable Body Sensor Networks[ C]. Washington, DC, USA: IEEE Computer Society, 2006. 72- 75.
[ 3] Wang Jau-Hsiung, GaoYang. Mult-i sensor data fusion for landvehicle attitude estimationusing a fuzzy expert system[ J]. Data Science Journa,l 2005, 4( 1): 127 -139.
[ 4] LuD,i Zeng Y,i YaoYu. Sensor management based oncross entropy[A]. Proceedings of the 20th IEEE InstrumentationandMeasurement Technology Confer-ence[ C]. Washington, DC, USA: IEEEComputer Society, 2003. 1555-1558.
[ 5] 代凤娟. 支持故障预测的传感器优化布置研究 [D]. 西安: 西北工业大学力学与土木建筑学院, 2007.
[ 6] 吴丹, 吴子燕,杨海峰, 等. 基于两步有效配置法的传感器优化布置[ J]. 西华大学学报(自然科学版), 2008, 27( 2): 48- 51.
[ 7] KiasiF, LucasC, FazlA. An interpolative fuzzy in-ference using least square principle by means of B-functionandhighorder polynomials[ A]. Mechatron-ics andAutomation, 2005 IEEE International Confer-ence[ C]. Washington, DC, USA: IEEEComputer Society, 2005. 545-550.
[ 8] 高维成, 徐敏建, 刘伟. 一种动态种群不对称交叉的新型遗传算法[ J]. 南京理工大学学报(自然科学版), 2007, 31( 4): 444-448.
[ 9] Kennedy J. Probability anddynamics in the particle swarm[A]. Proceedings of the 2004 IEEECongress on Evolutionary Computation[ C]. Los Alamitos, USA: IEEEComputer Society, 2004. 340-347.
[ 10] CervellinoA, GianniniC, GuagliardiA, et a.l Quant-i tative analysis of gold nanoparticles from synchrotron data bymeansof least-squares techniques[ J]. TheEu-ropeanPhysical JournalB, 2004, 41( 12): 485-493.
[ 11] SunJun, Feng Bin, XuWengbo. Particle swarmopt-i mizationwithparticles having quantumbehavior[A]. Proc of 2004 Congress on Evolutionary Computation [C]. Washington, DC, USA: IEEEComputer Socie-ty, 2004: 325-331.
[ 12] 屈百达, 焦竹青, 徐保国. 多量子粒子群协同优化算法研究[ J]. 计算机工程与应用, 2008, 44( 7): 72 -74.

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备注/Memo

备注/Memo:
基金项目: 国家/ 8630计划资助项目( 2006AA10A301)
作者简介: 蒋鼎国( 1964- ), 男,博士生, 副教授, 主要研究方向: 传感器管理, E-mail:hyitjdg@163. com; 通讯作者:徐保国(1950- ),男, 教授,博士生导师, E-mail: xbg@sytu. edu. cn。
更新日期/Last Update: 2012-11-19