基于灰自助模型的气压动态测量结果评估方法

通过融合灰色模型GM(1,1)、Bootstrap方法以及不确定度评定理论,建立了气压动态测量结果的灰自助评估模型GBM(1,1),并选取估计真值、估计区间和平均不确定度等参数描述其估计结果。实验结果表明,GBM(1,1)模型融合了灰色模型GM(1,1)和Bootstrap方法的优势,可以准确模拟动态测量数据的概率分布,并跟踪动态测量过程中被测量的变化趋势,其估计误差最大值和平均值均小于原始数据的测量误差最大值和平均值。区间估计的可靠度高于96%,估计区间能够较完整地包络被测量的动态波动范围,由此证明GBM(1,1)模型能够提高气压测量精度,并可对动态测量结果的不确定度做出准确评估。

Evaluation method for dynamic measurement result of atmospheric pressure based on grey bootstrap model

The grey bootstrap evaluation model GBM (1, 1) for dynamic measurement results of atmospheric pressure is built through fusing the grey model GM (1, 1), bootstrap method and uncertainty evaluation theory. The parameters, such as the estimated true value, estimated interval and mean uncertainty are selected to describe the estimation results. The experiment results indicate that the GBM (1, 1) model combines the advantages of the GM (1, 1) grey model and bootstrap method, can accurately simulate the probability distribution of dynamic measurement data and track the variation trends of the measured quantity during dynamic measurement progress. The maximum value and mean value of the estimated errors are smaller than those of the measurement errors of original data, respectively. The interval estimation reliability of the GBM (1, 1) model exceeds 96%, and the estimated interval can fully envelop the dynamic fluctuation range of the measured quantity, which proves that the GBM (1, 1) model can improve the measurement accuracy of atmospheric pressure and evaluate the uncertainty of dynamic measurement results accurately.