Grey evaluation of non-statistical uncertainty in multidimensional precision measurement

Qin, Ping; Shen, Yue; Wang, Zhongyu

doi:10.1007/s00170-005-0224-5

Cited by 13 publications

(4 citation statements)

References 5 publications

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“…For example, a polynomial fitting model [21,22] is proposed to predict the dynamic measurement uncertainty when lacking information. The grey system theory is used for measurement uncertainty evaluation with a small sample in dynamic measurement [23], multidimensional measurement [24], and dynamic filtering [25].…”

Section: Introductionmentioning

confidence: 99%

The grey relational approach for evaluating measurement uncertainty with poor information

Zhang

Wang

Zhou

et al. 2015

Meas. Sci. Technol.

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The Guide to the Expression of Uncertainty in Measurement (GUM) is the master document for measurement uncertainty evaluation. However, the GUM may encounter problems and does not work well when the measurement data have poor information. In most cases, poor information means a small data sample and an unknown probability distribution. In these cases, the evaluation of measurement uncertainty has become a bottleneck in practical measurement. To solve this problem, a novel method called the grey relational approach (GRA), different from the statistical theory, is proposed in this paper. The GRA does not require a large sample size or probability distribution information of the measurement data. Mathematically, the GRA can be divided into three parts. Firstly, according to grey relational analysis, the grey relational coefficients between the ideal and the practical measurement output series are obtained. Secondly, the weighted coefficients and the measurement expectation function will be acquired based on the grey relational coefficients. Finally, the measurement uncertainty is evaluated based on grey modeling. In order to validate the performance of this method, simulation experiments were performed and the evaluation results show that the GRA can keep the average error around 5%. Besides, the GRA was also compared with the grey method, the Bessel method, and the Monte Carlo method by a real stress measurement. Both the simulation experiments and real measurement show that the GRA is appropriate and effective to evaluate the measurement uncertainty with poor information.

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Section: Introductionmentioning

confidence: 99%

The grey relational approach for evaluating measurement uncertainty with poor information

Zhang

Wang

Zhou

et al. 2015

Meas. Sci. Technol.

Self Cite

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“…Significant relational grades tend to occur when changes are consistent, whereas inconsistent changes promote insignificant grades. Relational grading also compensates for the shortcoming caused by the systematic analysis of mathematical statistics [17,26,27]. Based on this concept, the present study created the reference variety with the overall desired traits to perform a grey relational analysis of the antioxidant capacities of different peach varieties.…”

Section: Discussionmentioning

confidence: 99%

Grey relational analysis and fuzzy synthetic discrimination of antioxidant components in peach fruit

Zhang

Shen

et al. 2018

ARCH BIOL SCI BELGRA

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Free phenolic compounds and total phenolic content were quantified using four stages of four blood-flesh and four non-blood-flesh peach fruits. Data were used to assess the oxidation resistance using grey relational analysis and fuzzy synthetic discrimination methods. Data from equal-weight and weighted evaluations calculated using both grey relational analysis and fuzzy synthetic discrimination were very similar. The weighted relational grade and weighted evaluation value of the overall resistance to fruit oxidation were ordered according to the weight coefficient method, which demonstrated that there were discrepancies in the ranking of oxidation resistance of the tested varieties between early and late fruit developmental stages. During fruit development, the blood-flesh varieties showed a relatively high overall resistance to oxidation, with the highest observed in Beijingyixianhong. The results suggest that both grey relational analysis and fuzzy synthetic discrimination have high applicability in assessing the resistance to oxidation of peach varieties.

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“…Evaluation these control measures is a systematic determination of merit, worth, and significance of these control steps using criteria against a set of standards, which make next round of control even more intelligent [17] . Figure 4.…”

Section: G Grey Control Evaluationmentioning

confidence: 99%

The Intelligent Control and Modeling of a Traffic Circle

Zeng

Zheng

2009

2009 International Conference on Information Engineering and Computer Science

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This article paid more attention to the confliction of the flowing in and out for the circle, and put forward new methods to control vehicles flow by setting temporary parking area (abbreviated as TPA) in the circle and setting traffic lights. The multiple goal function emphasizes the principle that the number of the waiting vehicles is the least and while the efficiency of the vehicles out of the circle is the most. The characteristics of the traffic flow in general traffic circle were analyzed in this paper. Firstly, used a simplified traffic flow model to describe the weaving sections of the traffic circle. Then, the capacity of the traffic circles was determined by using linear or nonlinear optimization algorithm. Finally, strengths and weaknesses of this control system were analyzed.

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Grey evaluation of non-statistical uncertainty in multidimensional precision measurement

Cited by 13 publications

References 5 publications

The grey relational approach for evaluating measurement uncertainty with poor information

The grey relational approach for evaluating measurement uncertainty with poor information

Grey relational analysis and fuzzy synthetic discrimination of antioxidant components in peach fruit

The Intelligent Control and Modeling of a Traffic Circle

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