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標(biāo)題: Titlebook: Data Modeling for Metrology and Testing in Measurement Science; Franco Pavese,Alistair B. Forbes Book 2009 Birkh?user Boston 2009 Internet [打印本頁]

作者: Lipase    時間: 2025-3-21 16:57
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Daniel C. O’Connell,Sabine Kowal measurement comparisons. Examples illustrate the power of the techniques in extending uncertainty analysis to cases where the applicability of the usual methods is in doubt, such as consistency testing using chi-squared-like statistical aggregates.
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作者: 圓木可阻礙    時間: 2025-3-23 00:21
Modelling of Measurements, System Theory and Uncertainty Evaluation, of disregarding nonlinearities and time-variant (dynamic) behaviour. The chapter demonstrates that, based on carefully analysing and understanding the measurement, it is possible to reach proper modelling of measurements and one may sufficiently describe the relevant effects of imperfect modelling.
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作者: 構(gòu)成    時間: 2025-3-23 22:54
2164-3679 of fields, including chemistry, software engineering, and mThe aim of this book is to provide, ?rstly, an introduction to probability and statistics especially directed to the metrology and testing ?elds and secondly, a comprehensive, newer set of modelling methods for data and uncertainty analysis
作者: 項目    時間: 2025-3-24 04:19
The Cognitive and Behavioural Sciencesmena or process. This chapter deals with the different types of description of the uncertainty components, with a wide selection of citations from reference international documents, and then with the different models corresponding to the different data characteristics. An extended bibliography is included.
作者: Myocyte    時間: 2025-3-24 07:07
https://doi.org/10.1007/978-0-387-77632-3ual instruments and with the different forms of their implementation. Both the hardware and software components of a virtual instruments are detailed. A short reference to virtual laboratories is also included.
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作者: 噴出    時間: 2025-3-24 20:38
Probability in Metrology,ecent results that make a systematic use of probability an appropriate logic for measurement. It is suggested that these two mainstreams may ultimately converge in a unique theory of measurement, formulated in a probabilistic language and applicable to all domains of science.
作者: 無聊點好    時間: 2025-3-25 00:27
,Frequency and Time—Frequency Domain Analysis Tools in Measurement,pace or time localization of short-lived repeating patterns. These are signal-processing tools which require some good understanding of the underlying theory to avoid common pitfalls and circumvent some limitations. Examples are given to show applicability.
作者: bonnet    時間: 2025-3-25 03:54
The Cognitive and Behavioural Sciencesaccording to models that are different according to the underpinning assumptions, which must adequately match the characteristic of the observed phenomena or process. This chapter deals with the different types of description of the uncertainty components, with a wide selection of citations from ref
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作者: 舊石器    時間: 2025-3-25 16:28
Communicating for Social Changerement error is located on the interval [-Δ,Δ]. The traditional engineering approach to such situations is to assume that Δ . is uniformly distributed on [-Δ,Δ], and to use the corresponding statistical techniques. In some situations, however, this approach underestimates the error of indirect measu
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https://doi.org/10.1007/978-3-319-76017-9one that weighs each alternative pros, cons, and risks. The support for decision-making is data that come basically from experience, either previously acquired or gathered for the specific decision-making. The data usually come from different sources and thus have to be fused for a single decision.
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作者: FEAT    時間: 2025-3-26 14:56
From Monologism to Dialogicality; it is always reduced to relevant influences, system parameters, and behaviour. Therefore, in uncertainty evaluation, it is important to consider the effects of imperfect modelling. Derived from the classical theory of signals and systems, this contribution explains the basic approaches to systemat
作者: Unsaturated-Fat    時間: 2025-3-26 17:47
Daniel C. O’Connell,Sabine Kowal been expressed (either explicitly or implicitly) as probability density functions, Monte Carlo techniques can propagate uncertainties through any measurement equation or algorithm – including statistical aggregates. These techniques are introduced in this chapter, and applied to examples drawn from
作者: 剝皮    時間: 2025-3-27 00:26
Daniel C. O’Connell,Sabine Kowalata obtained through measurement are transferred via communication networks and processed further bysoftware systems. This development has led to increasingly complex and distributed metrological functions. This complexity has different facets: it can not only enhance the functionality of a measurin
作者: CURT    時間: 2025-3-27 05:01
https://doi.org/10.1007/978-0-387-77632-3ware component gives the hardware extended measuring capabilities and the instruments are thus named virtual instruments. This chapter deals with virtual instruments and with the different forms of their implementation. Both the hardware and software components of a virtual instruments are detailed.
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作者: 讓步    時間: 2025-3-27 12:30
Data Modeling for Metrology and Testing in Measurement Science978-0-8176-4804-6Series ISSN 2164-3679 Series E-ISSN 2164-3725
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Approaches to Data Assessment and Uncertainty Estimation in Testing,The following chapter presents a selection of feasible approaches to data assessment and uncertainty evaluation for single measurands (univariate case), multiple measurands with and without a functional relationship (multivariate case), and some aspects of semi-qualitative and qualitative testing.
作者: 注意    時間: 2025-3-28 15:39
Franco Pavese,Alistair B. ForbesTakes the reader beyond mainstream methods described in standard texts on data and uncertainty analysis.Real-world applications in a variety of fields, including chemistry, software engineering, and m
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2164-3679 k lends itself as a possible textbook for undergraduate or postgraduate study in an area where existing texts focus mainly on the most common and well-known methods that do not encompass modern approaches to ca978-0-8176-4804-6Series ISSN 2164-3679 Series E-ISSN 2164-3725
作者: 食物    時間: 2025-3-29 12:58
Rikki Lee B. Mendiola,Pamela A. Custodiol paradigms under which different methods for uncertainty assessment are described include the frequentist, Bayesian, and fiducial paradigms. Each approach is illustrated using common examples and computer code for carrying out each analysis is illustrated using open-source software.
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Book 2009ta analysis, allowing a deeper understanding of complex situations in measurement. The book lends itself as a possible textbook for undergraduate or postgraduate study in an area where existing texts focus mainly on the most common and well-known methods that do not encompass modern approaches to ca
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作者: bonnet    時間: 2025-3-30 18:16
Probability in Metrology,ly participated in the development of statistic–probabilistic disciplines, not only adopting principles and methods, but also contributing with new and influential ideas. Two mainstreams of studies are identified in the science of measurement. The former starts with the classical theory of errors an
作者: 合唱隊    時間: 2025-3-30 22:24
Three Statistical Paradigms for the Assessment and Interpretation of Measurement Uncertainty,pment and adoption of the ISO ., there will always be a need to improve the assessment of uncertainty in particular applications and to extend it to cover new areas. Among other work along these lines, the International Committee on Weights and Measures?’ Joint Committee on Guides in Metrology is cu
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作者: 閑蕩    時間: 2025-3-31 05:54
Parameter Estimation Based on Least Squares Methods,it is shown that for many problems for which there are correlated effects it is possible to develop algorithms that use structure associated with the variance matrices to solve the problems efficiently. It is also shown how least squares methods can be adapted to cope with outliers.
作者: headway    時間: 2025-3-31 12:31





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