摘要
提出一种自身定位参数优化方法,首先利用遗传算法在全局寻优方面的优势,改善了无线传感器网络中节点自身位置信息的定位精度欠佳问题,其次,遗传算法利用优化方法,初始种群优化、调整适应度的选取运算、引入错误校正因子等,对节点自身位置进行精确定位,从而有效提升节点定位精度和稳定性。实验结果表明,在测距阶段和定位阶段均取得了一定进展。该方法将位置问题建立在不同的距离或路径的基础上,以求得最优解,从而克服了传统以数理统计为主的局限性,同时能够保证系统的性能,节省网络资源。
The proposed self-localization parameter optimization method in this study firstly improves the accuracy of node self location information in wireless sensor networks by utilizing the advantages of genetic algorithm in global optimal solutions.Secondly,the genetic algorithm uses optimization methods such as optimizing the initial population,adjusting the selection operation of fitness,and introducing error correction factor,achieving precise positioning of node location,thereby effectively improving the accuracy and stability of node location.Experimental results show a certain progress in both the distance measurement stage and the location stage.Fundamentally,this method builds location problems on the basis of different distances or paths to obtain the optimal solution,thereby overcoming the limitation of traditional methods that rely mainly on mathematical-statistical methods.Furthermore,this method can ensure the system performance and save network resources.
作者
樊荣
FAN Rong(Zhumadian Vocational and Technical College,Zhumadian,Henan,China 463000)
出处
《湖南邮电职业技术学院学报》
2023年第2期5-8,共4页
Journal of Hunan Post and Telecommunication College
基金
2021年度河南省高等学校重点科研项目计划课题“高职教师信息化素养培育体系建构研究”(课题编号:21B880052)。
关键词
无线传感器网络
遗传算法
网络节点自身定位
参数优化
wireless sensor networks
genetic algorithm
self-localization of network nodes
parameter optimization
