期刊论文

Shang, Y.

中文

北京邮电大学学报

1007-5321

2023

46

1

90-96

10.13190/j.jbupt.2021-319

湖南省市联合自然科学基金项目（2021JJ50093）； 国家自然科学基金项目（11875164）； 湖南省重点研发计划项目（2018SK2055）；

本校为第一机构

针对群智能优化算法在无线传感器网络(WSN)定位问题中迭代效率慢和容易陷入局部最优等问题,提出了临时优劣重心反向融变的麻雀优化WSN定位算法。该算法利用节点估计距离构建盒子模型,初步确定节点的位置区域,缩小了前期的搜寻区...展开更多 针对群智能优化算法在无线传感器网络(WSN)定位问题中迭代效率慢和容易陷入局部最优等问题,提出了临时优劣重心反向融变的麻雀优化WSN定位算法。该算法利用节点估计距离构建盒子模型,初步确定节点的位置区域,缩小了前期的搜寻区域范围;利用Circle混沌映射初始化种群,使种群分布更加均匀;并提出临时优劣重心反向学习策略,在充分利用种群的搜索经验的同时也保...

To solve the issues of that swarm intelligence optimization algorithm has low iterative efficiency and is easy to fall into local optimum in wireless sensor network(WSN) localization, WSN localization algorithm is proposed based on temporary best and worst centroid oppo...MORE To solve the issues of that swarm intelligence optimization algorithm has low iterative efficiency and is easy to fall into local optimum in wireless sensor network(WSN) localization, WSN localization algorithm is proposed based on temporary best and worst centroid opposite cross mutation and sparrow optimization. The al...