Multi-response-model confirmation measurement method based on probability box frame

A measurement method and response model technology, applied in special data processing applications, complex mathematical operations, instruments, etc., to achieve high computing efficiency, effectively confirm the measurement, and avoid the effect of obtaining the process

Inactive Publication Date: 2018-08-21
XIAMEN UNIV
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However, existing probability box methods addr...

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  • Multi-response-model confirmation measurement method based on probability box frame
  • Multi-response-model confirmation measurement method based on probability box frame
  • Multi-response-model confirmation measurement method based on probability box frame

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Embodiment Construction

[0052] The following embodiments will further illustrate the present invention in conjunction with the accompanying drawings.

[0053] The present invention comprises the following steps:

[0054] 1) According to the relevant theories and input conditions of the specific problem, establish the corresponding simulation calculation model;

[0055] 2) Divide the model input parameters into random uncertainty, cognitive uncertainty and mixed uncertainty, and evaluate each parameter to determine its specific distribution;

[0056] 3) Perform M×N double-layer sampling on the model to obtain multi-dimensional samples output by M groups of models;

[0057] The specific implementation process is as figure 1 Shown: First, the cognitive uncertainty of the outer layer is sampled once; then, the random uncertainty of the inner layer is sampled N times, and the corresponding sample value is calculated; the above process is repeated for M times of outer layer sampling , and finally obtain...

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Abstract

A multi-response-model confirmation measurement method based on a probability box frame comprises the steps that corresponding simulating calculation models are established according to relevant theories and input conditions of concrete problems; input parameters of the established corresponding simulating calculation models are divided into random uncertainty, cognition uncertainty and mixture uncertainty, and the parameters are evaluated to determine specific distribution; M*N double-layer sampling is conducted on the models to obtain multi-dimensional samples of M sets of models; mahalanobis distance conversion is conducted on each set of samples to obtain mahalanobis distance samples; the mahalanobis distance sample values are countered; an area measurement interval of two probabilityboxes is calculated. By adopting a probability box method, the simultaneously existing problem of random uncertainty and cognition uncertainty can be effectively described, existing probability modelsand interval number and evidence structures can be directly converted into the forms of probability boxes, uncertainty description conforms to project customs and is easily accepted and used by project workers.

Description

technical field [0001] The invention relates to a measurement method, in particular to a multi-response model confirmation measurement method based on a probability box framework, which is suitable for multi-input multi-output model confirmation measurement. Background technique [0002] In the face of increasingly large and complex engineering systems, it is difficult and expensive to conduct physical experiments on them. In engineering research, researchers try to use increasingly mature computer technology for modeling and simulation calculations, and replace complex and expensive real physical experiments by calculating the built models. However, when establishing a calculation model, the model is usually simplified due to the existing technology and calculation efficiency, or due to the cognitive limitations of the modeler, there is a certain deviation between the built model and the actual model. At this time, the accuracy and credibility of the calculation model will...

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Application Information

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IPC IPC(8): G06F17/50G06F17/18
CPCG06F17/18G06F30/20
Inventor 苏国强张保强陈庆邓振鸿陈梅玲
Owner XIAMEN UNIV
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