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双保真KLE代理模型结合主动学习用于随机场
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2026年10月5日,arXiv Statistics Machine Learning(一手来源)报道了一种用于随机场的双保真 Karhunen-Loève 展开代理模型与主动学习方法(BF-KLE-AL)。该方法用 Karhunen-Loève 展开(KLE)与多项式混沌展开(PCE)保持输入不确定性到输出标量场的显式映射,并以少量高保真(HF)仿真修正低保真(LF)模拟的系统偏差。目前报道仅给出方法框架,未披露具体算例、精度对比或代码数据等后续验证信息。
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LatestOct 5
提出BF-KLE-AL方法,以KLE与PCE构建显式映射并用少量HF仿真修正LF偏差。Timeline
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Oct 5, 2026
- arXiv · Statistics Machine Learning用于随机场的双保真 Karhunen-Loève 展开代理模型与主动学习方法
提出双保真 Karhunen-Loève 展开代理模型(BF-KLE-AL),用 KLE 与多项式混沌展开(PCE)保持输入不确定性到输出标量场的显式映射,并以少量高保真(HF)仿真修正低保真(LF)模拟的系统偏差。
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