一个智能成本参考粒子过器,可重新采样多人群合作
Xinyu Zhang1,2, Mengjiao Ren1,2, Jiemin Duan1,2
1Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an 710048, China.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
本研究介绍了一种智能成本参考颗粒过器 (CRPF),使用多种群的合作来提高状态估计的准确性. 这种新的方法提高了粒子多样性,并降低了对初始值的灵敏度,超过了现有的CRPF算法.
科学领域:
- 信号处理 信号处理
- 计算智能是一种计算智能.
- 国家估计.
背景情况:
- 成本参考粒子过器 (CRPF) 对于未知噪声统计数据的状态估计是有效的.
- 由于粒子多样性和初始值灵敏度,CRPF的准确性受到限制.
研究的目的:
- 提出一个智能CRPF算法,使用多人群合作来解决CRPF的局限性.
- 在状态估计问题中提高估计准确性和稳定性.
主要方法:
- 开发了一种具有环状结构的多人群合作重新采样策略.
- 实施了金色截面比用于粒子重量分类 (高,中,低).
- 利用高斯基基因突变重新采样低重粒子,结合人群间合作.
主要成果:
- 拟议的智能CRPF降低了对初始粒子值的灵敏度.
- 在重新采样过程中增强了粒子多样性.
- 与一般CRPF和MH-CRPF相比,实现了较低的根平均平方误差 (RMSE) 和平均绝对误差 (MAE).
结论:
- 多人群合作CRPF算法有效地提高了状态估计的准确性.
- 该方法在现有CRPF技术上表现出卓越的性能和稳定性.
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