摘要
针对多阅读器竞争共享介质和覆盖区域重叠造成射频信号干扰和碰撞的问题,依据阅读器在识别范围内受干扰的程度,将其设定为稀疏或稠密阅读器,给出双层规划阅读器避碰模型,并提出相应的双层规划混合智能优化算法。将鱼群算法的拥挤度和追尾行为引入免疫优化算法中,增强群体的局部勘探能力,获得免疫鱼群优化算法;进而,将此算法作为算子模块嵌入到遗传算法中,得到求解此避碰模型的混合智能优化算法。比较性的数值实验显示,该算法的搜索效果稳定且具有明显优势。
Aiming at the problem of radio-frequency signal interference and collision caused by multi-reader's competing shared communications medium and coverage area overlap,this study designs a bi-level programming reader collision avoidance model and proposes a new bi-level hybrid intelligent optimization approach to solve the optimal collision avoidance scheme.The model includes sparse and dense readers defined in virtue of readers'interference degree within their identification regions.Based on the basic framework of genetic algorithm,the approach also includes a new immune fish swarm approach,acquired by embedding the fish swarm algorithm's crowding degree and rear-end behavior into a basic immune optimization algorithm in order to promote the local exploitation of population.Numerically comparative experiments have validated that the proposed bi-level optimization approach is of strong stability and can win over the compared approaches.
作者
王垚
张著洪
WANG Yao;ZHANG Zhuhong(College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China)
出处
《贵州大学学报（自然科学版）》
2020年第4期79-85,共7页
Journal of Guizhou University:Natural Sciences
基金
国家自然科学基金资助项目(61563009)。
关键词
多阅读器
避碰
免疫优化
鱼群算法
识别范围
multi-reader
collision avoidance
immune optimization
fish swarm algorithm
identification range
作者简介
王垚(1995-),男,在读硕士,研究方向:智能信息处理,Email:1531431965@qq.com;通讯作者:张著洪,Email:zhzhang@gzu.edu.cn.
