粒子群优化算法(Particle Swarm Optimization, PSO)作为一种高效的全局优化算法,已被广泛应用于温室系统模型的优化与控制中,近年来在温室系统计算流体动力学(Computational Fluid Dynamics, CFD)模型中也得到了应用。本文综述了粒子群算法的基本原理及其在温室系统CFD模型中的应用进展,分析总结了粒子群算法在温室系统CFD模型中应用的特点、优势,以及面临的挑战,并对未来的研究方向提出了展望。Particle Swarm Optimization (PSO), as an efficient global optimization algorithm, has been widely used in the optimization and control of greenhouse system models. In recent years, it has also been applied in Computational Fluid Dynamics (CFD) models of greenhouse systems. This article summarizes the basic principles of particle swarm optimization algorithm and its application progress in greenhouse system CFD models. It analyzes and summarizes the characteristics, advantages, and challenges of particle swarm optimization algorithm in greenhouse system CFD models, and puts forward prospects for future research directions.
