精品文档---下载后可任意编辑一类改进的粒子群优化算法对混沌系统未知参数的估量中期报告（This is a mid-term report on the estimation of unknown parameters in chaotic systems using an improved particle swarm optimization algorithm）摘要：本文介绍了一种改进的粒子群优化算法，并将其应用于混沌系统的未知参数估量问题。在标准粒子群优化算法的基础上，本文提出了一种自适应权重策略，并结合多样性维护机制，以加快算法的收敛速度和提高算法的全局搜索能力。通过在多个已知混沌系统上的实验结果，本文验证了所提出算法的有效性和鲁棒性。关键词：粒子群优化；混沌系统；未知参数估量；自适应权重策略；多样性维护机制Abstract：This paper introduces an improved particle swarm optimization algorithm and applies it to the estimation of unknown parameters in chaotic systems. Based on the standard particle swarm optimization algorithm, this paper proposes an adaptive weight strategy and combines it with a diversity maintenance mechanism to speed up converge and improve global search ability. Through experiments on multiple known chaotic systems, this paper verifies the effectiveness and robustness of the proposed algorithm.Keywords: Particle Swarm Optimization; Chaotic System; Unknown Parameter Estimation; Adaptive Weight Strategy; Diversity Maintenance Mechanism
