Multi-topology hierarchical collaborative hybrid particle swarm optimization algorithm for WSN

CHINA COMMUNICATIONS(2023)

引用 0|浏览5
暂无评分
摘要
Wireless sensor networks (WSN) are widely used in many situations, but the disordered and random deployment mode will waste a lot of sensor resources. This paper proposes a multi-topology hierarchical collaborative particle swarm optimization (MHCHPSO) to optimize sensor deployment location and improve the coverage of WSN. MHCHPSO divides the population into three types topology: diversity topology for global exploration, fast convergence topology for local development, and collaboration topology for exploration and development. All topologies are optimized in parallel to overcome the precocious convergence of PSO. This paper compares with various heuristic algorithms at CEC 2013, CEC 2015, and CEC 2017. The experimental results show that MHCHPSO outperforms the comparison algorithms. In addition, MHCHPSO is applied to the WSN localization optimization, and the experimental results confirm the optimization ability of MHCHPSO in practical engineering problems.
更多
查看译文
关键词
particle swarm optimizer,levy flight,multi-topology hierarchical collaborative framework,lamarckian learning,intuitive fuzzy entropy,wireless sensor network
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要