基于高斯过程的多忠度贝叶斯优化,以获得最佳的校准点选择
Hua Zhuo1, Jungang Ma1, Mei Yang1
1Xinjiang Uygur Autonomous Region Research Institute of Measurement & Testing, Urumqi 830000, China.
Sensors (Basel, Switzerland)
|November 27, 2025
概括
本研究介绍了基于高斯过程的多忠度贝叶斯优化 (GP-MFBO) 框架,以优化温度和湿度校准点. 这种新方法显著提高了校准室的统一性得分和预测准确度.
科学领域:
- 计量学 计量学 计量学
- 环境工程 环境工程
- 优化技术 优化技术
背景情况:
- 温度和湿度校准室对于航空航天和生物医学至关重要.
- 传统的校准方法的范围有限,效率低.
- 现有的方法很难适应复杂的操作要求.
研究的目的:
- 开发一个先进的框架,以最佳选择温度和湿度校准点.
- 解决传统固定校准点在适应性,覆盖范围和效率方面的局限性.
- 为了提高校准室的可靠性和准确性.
主要方法:
- 基于高斯过程的多忠度贝叶斯优化 (GP-MFBO) 框架的开发.
- 整合一个三层渐进式多忠度建模系统 (分析,CFD,实验).
- 实施系统的不确定性量化和适应性获取函数.
主要成果:
- GP-MFBO 实现了最佳的校准点,温度均度为 0.149 和湿度均度为 2.38.
- 与其他方法相比,一致性得分的提高高达81.7% (温度) 和76.3% (湿度).
- 预测置信区间覆盖率达到94.2%,超过了比较方法.
结论:
- GP-MFBO框架为优化校准点选择提供了一个强大的解决方案.
- 这项研究为大型空间温度和湿度校准系统的科学设计提供了基础.
- 拟议的方法提高了仪器测试和验证的效率和准确性.
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