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Parameter probability uncertainty modeling method under data deletion

A technology of uncertainty and modeling methods, which is applied in special data processing applications, complex mathematical operations, design optimization/simulation, etc. It can solve the problems of repeated iterations of modeling accuracy levels, and achieve quantitative measurement of effective probability uncertainty Effects of models, practical methods

Pending Publication Date: 2022-03-29
BEIHANG UNIV
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Problems solved by technology

Among them, the uncertainty modeling method based on the EM algorithm has good parameter estimation properties, so it is the most commonly used in engineering practice, but the modeling accuracy level of this method is related to the selection of the initial value and requires repeated iterations

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  • Parameter probability uncertainty modeling method under data deletion
  • Parameter probability uncertainty modeling method under data deletion
  • Parameter probability uncertainty modeling method under data deletion

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Embodiment Construction

[0061] The present invention is further described with reference to the accompanying drawings.

[0062] Step 1: Obtain the observation samples of product parameters, determine the censored data information of the observation samples, and select the probability distribution type corresponding to the dispersion characteristics of the parameters;

[0063] The data collected and recorded in the field test of a certain key parameter of the product or the data obtained by simulation are used as observation data, and then the probability distribution type of the key parameter is determined based on engineering experience, such as geometric size parameters, material performance parameters, etc., often obey the normal distribution, mechanical The life parameters of products often obey the Weibull distribution, and the life parameters of electronic products often obey the exponential distribution.

[0064] Step 2: Carry out m resampling operations with replacement based on the Bootstrap...

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Abstract

The invention provides a parameter probability uncertainty modeling method under data deletion, which mainly comprises the following steps of: (1) acquiring an observation sample of a product parameter, and selecting a probability distribution type corresponding to the dispersity of the observation sample; (2) carrying out replacement resampling on the original data based on a Bootstrap method, and respectively carrying out maximum likelihood estimation by adopting an EM method so as to construct an initial probability distribution model; (3) establishing conditional probability distribution of the censored data based on each initial probability distribution model, and carrying out random sampling to replace the censored data so as to construct a complete data set; (4) respectively carrying out maximum likelihood estimation on the complete data set to construct an alternative probability distribution model; and (5) selecting the probability distribution model with the maximum information entropy from the alternative probability distribution models as an uncertainty representation model of the original data. The invention provides a simple and effective probabilistic uncertainty quantitative measurement method for the observation data sample containing the censored data.

Description

[0001] Technical field [0002] The invention relates to the field of statistical analysis of reliability data, in particular to a parameter probability uncertainty modeling method under censored data. Background technique [0003] Affected by time cost, economic cost, technical level and human factors, the actual data information available for engineering is often in a censored state. For example, when testing some material parameters or size parameters, due to the limitation of the test equipment range, the test information beyond the equipment range cannot be obtained, resulting in censored data; when testing certain load parameters in extreme environments, the test equipment Due to the influence of environmental conditions, the sensitivity is reduced, and the test data below a certain value may not be fed back when measuring certain ranges of data, resulting in censored data; when carrying out reliability verification tests, the tested samples Due to the constraints of hi...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06F17/18
CPCG06F30/20G06F17/18
Inventor 钱诚李文娟任羿孙博王自力
Owner BEIHANG UNIV
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