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

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