基于改进蝴蝶优化算法的无线传感网络节点定位的研究  

Research on Wireless Sensor Network Node Localization Based on Improved Butterfly Optimization Algorithm

作　　者：宋芳琴[1] Song Fangqin(Shaoxing Vocational&Technical College,Shaoxing 312000,Zhejiang,China)

机构地区：[1]绍兴职业技术学院,浙江绍兴312000

出　　处：《科技通报》2025年第4期30-35,57,共7页Bulletin of Science and Technology

基　　金：国家自然科学基金项目(42377136)。

摘　　要：如何更好地进行节点定位一直都是无线传感网络研究的主要方向。针对当前节点定位精度低的缺点,提出了基于改进蝴蝶优化算法的节点定位策略。首先,阐述了DV-HOP (distance vector-hop)定位算法模型;其次,针对蝴蝶优化算法存在收敛速度慢,容易陷入局部最优的缺点,采用了基于Logistic混沌初始化、转换概率优化和引入自适应权重3个方面进行了算法优化;最后,仿真结果说明该算法相比于BOA (butterfly optimization algorithm),CBOA (chef-based optimization algorithm),ABOA算法在节点总数、锚节点比例和通信半径指标下具有较好的优势,提高了节点定位精度。How to better node localization has always been the main direction of wireless sensor network research.Aiming at the current shortcomings of low node positioning accuracy,a node positioning strategy based on the improved butterfly optimization algorithm is proposed.Firstly,the DV-HOP(distance vector-hop) localization algorithm model is elaborated,secondly,for the shortcomings of butterfly optimization algorithm,which has slow convergence speed and is easy to fall into the local optimum,the algorithm is optimized based on the three aspects of Logistic Chaos Initialization,Conversion Probability Optimization and the introduction of Adaptive Weights.Finally,the simulation results illustrate that the algorithm has a better advantage over BOA(butterfly optimization algorithm),CBOA(chef-based optimization algorithm),and ABOA algorithms in terms of the total number of nodes,the proportion of anchor nodes,and the communication radius index,and improves the node localization accuracy.

关 键 词：无线传感网络 节点定位 混沌初始化 

分 类 号：TP393.04[自动化与计算机技术—计算机应用技术]