Comparison of Interval Analysis and Standard Statistical Methods for Estimating Experimental Data with Uncertainty

被引：0
|
作者：
Kumkov, S. I. [1 ,2 ]
Jaulin, L. [3 ]
机构：
[1] Russian Acad Sci, Ural Branch, Krasovskii Inst Math & Mech, Ekaterinburg, Russia
[2] Ural Fed Univ, Ekaterinburg, Russia
[3] ENSTA Bretagne, Brest, France
来源：
MEASUREMENT TECHNIQUES | 2019年 / 62卷 / 02期
关键词：
interval analysis; statistical methods; noisy data; uncertainty conditions; process parameters; estimation;
D O I：
10.1007/s11018-019-01593-2
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Interval analysis procedures are used to estimate the parameters of an experimental chemical process under conditions of noise and uncertainty in the probabilistic characteristics of the measurement errors for a small measurement sample. Interval analysis makes it possible to describe exactly the set of admissible values of the estimated parameters needed for correct organization of the technological process through a correct choice of its parameters. Approximate estimates of the parameters are obtained by formal application of a statistical approach and it is shown that in this case the standard statistical approach yields essentially meaningless estimates for the parameters of the process studied here.
引用
收藏
页码：105 / 110
页数：6
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