Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (5): 268-270.

Previous Articles    

Particle swarm optimization based on cosine adaptive adjusting inertia weight and its application research in optimal sensor placement of historic architecture

LU Yang1, ZHANG Xiaoli2   

  1. 1.Computing Center, Henan University, Kaifeng, Henan 475000, China
    2.School of Computer and Information Engineering, Henan University, Kaifeng, Henan 475000, China
  • Online:2013-03-01 Published:2013-03-14

CW-PSO及其在古建筑传感器优化配置中的应用研究

路  杨1,张晓丽2   

  1. 1.河南大学 计算中心,河南 开封 475000
    2.河南大学 计算机与信息工程学院,河南 开封 475000

Abstract: Aiming at the premature convergence problem and unbalance of global search and local search in particle swarm optimization algorithm, this paper proposes a particle swarm optimization algorithm based on cosine adaptive adjusting inertia weight. The improved particle swarm optimization is applied in optimal sensor placement of wooden historic architecture. Simulation results show that it can avoid premature convergence to an extent, improve the global search ability and obtain accurate results of optimization by simulation experiment.

Key words: particle swarm optimization algorithm, inertia weight, wooden historic architecture, optimal sensor placement

摘要: 针对粒子群优化算法容易陷入早熟收敛以及全局搜索和局部搜索平衡能力差等缺点,提出了基于余弦自适应调整惯性权重的粒子群优化算法(CW-PSO),并将其应用在木构古建筑传感器优化配置中。仿真结果表明,该算法在一定程度上避免了早熟收敛,提高了全局和局部搜索性能,又能得到较为精确的寻优结果。

关键词: 粒子群优化算法, 惯性权重, 木构古建筑, 传感器优化配置