Confidence factors

Each topology has predictable voltage and current stresses for the power switches and rectifiers. These estimates have about a 90 percent confidence factor. Selecting the power devices at this stage in the design cycle can save precious time later in the program by not having to wait for parts. Table 3-2 contains equations that may be conservative in nature, but will work in the application. 

SUGGEST Adjust the property s value using the listed confidence factor... 

The inference engine was designed to use multivalued logic, i.e., it handles inexact reasoning. Confidence factors (CF) are contained in the THEN clauses of each rule. The equation for combining positive confidences is ... 

It would appear from Table I that the available comparison data are just as variable as data obtained with the differential thermal analyzer. The second index of variability, the 95% confidence factor, is a measure of the expected precision for the estimated vapor pressure at 25°C. (or melting point). This includes not only the variation of the experimental points from the regression line but also the uncertainty in the slope of that line. This latter factor has a progressively greater effect as the line is extended—i.e., the further the extrapolation is carried beyond the experimental data. For ethylene dibromide, for example, there is a 95% probability of the vapor pressure lying between 12.0 and 12.8 (12.4 -r-1.032 and 12.4 X 1.032). 

As a result of these studies reactors of different sizes could be operated with factors of scale that had a high confidence factor. 

It is widely accepted that probabilistic approach was first developed and applied in expert systems MYCIN and PROSPECTOR. In these expert systems the likelihood estimates are calculated for several competitive hypothesis H on the basis of available evidences E. In the expert system MYCIN each hypothesis was estimated by a confidence factor CF(H Ei,E2. . . ) as a difference of estimates for the measure of belief MB P[ Ei,E2,. .) and the measure of distrust MD P[ Ei,E2,...) ... 

The detection limit (DL) is the smallest concentration that can be reported with a certain level of confidence. Every analytical technique has a detection limit. For methods that employ a calibration curve, the detection limit is defined as the analyte concentration yielding a response of a confidence factor k higher than the standard deviation of the blank, as given in Equation 8-22. 

Rules and Confidence Factors. Facts that are known to the system are given a confidence level of either 0 (not true) or 100 (true). Facts that are not yet known to the system are assigned a confidence level of -1, and facts that are declared unknown are given a confidence level of -2. CORA was not structured to ask users for a degree of confidence in their answers. Each rule s conclusion is assigned either 0 if the rule fails or 100 if the rule succeeds. In that respect, CORA is not designed to deal with "fuzzy reasoning."... 

Fig. 13. Palaeoceanographic Proxy Confidence Factor Phase Chart (PPCFPC), as proposed by Elderfield (2002). The chart shows the relationship between time since the proxy was proposed, and confidence in the proxy. Initially, confidence is high. As the proxy relationship is explored in more detail, problems start to emerge and proxy confidence falls. At some point in time, many of these issues are ironed out, and proxy confidence can be reliably assessed. It is generally never as great as first thought ...

No. of Observations Efficiency Range Deviation Factor, Kr Range Confidence Factor (/) ... 

Silicone sealants retain their excellent adhesion properties and their excellent nonconductlve or insulation properties upon aging under heat and in harsh environments, again because of the stable bonds formed internally and to the substrate. The limits have not been fully established, but actual in-use applications have surpassed 15-20 years without a significant change.— This results in a confidence factor that is very important to the quality specifier, engineer or owner who is interested in cost-effective construction with long-term usability. 

Given the value functions, the weighted BR score S = S (1 W) is a random variable. Based on the observed values for K S = S(y, W). The benefit-risk comparison between treatment options will be made based on S. When there are no data available on W, several statistical indices were proposed to facilitate such comparison (Tervonen et al. 2011) rank acceptability index, center weight vectors, and confidence factors. 

Finally, the confidence factor, pf, is defined as fhe probabilify fhaf alternative i is ranked first when the weight vector is the same as w,-. It represents how the data (criteria values) can discern each treatment option. Treatment options with low first-rank acceptability indexes and small confidence factors are unlikely to be considered as the preferred alternative. 

In practice, if there exists information on fhe weighfs, eifher having an expected weight or having a preference order of benefifs and risks, the rank acceptability index can be used to compare the alternatives. Otherwise, if no preference information is available, fhe cenfral weighf vectors and confidence factors can be used to explore comparisons of fhe alternatives to assist the BRA. 

Equation 59.23 can be solved for the number of power cycles to fail, which yields a value of 1,311 power cycles or 107.8 years. It is important to employ a confidence factor (safety factor). Taking 2 as a standard safety factor, the final fatigue life is estimated at 53.9 years. 

Expert judgement plays a vital role in this process. However, the developer or the assessor can never be 100% certain that all hazards were mitigated. Furthermore, uncertainties might exist from secondary issues, such as who created the safety case, who was responsible for generating the evidence, what types of tools and techniques were used, etc. These confidence factors often tend to be implicit considerations in the development and assessment of safety cases. 

A fractile value f/ characterizes a certain characteristic value below or above which only a certain percentage s of all measured values are found. Such a fractile value can, however, be stated only with a certain confidence factor or degree of confidence W, because the fractile value is determined by only a limited amount of information. The fractile value can be formulated as follows ... 

Establishment of a confidence factor through experience and correlation with other data/information, such as NDE, failure analysis, and plant operational parameters... 

In the safety verifications, mean values of mechanical properties of existing materials derived from in situ tests and other sources of information, like available documentation or relevant sources, shall be used, taking into account the confidence factors (CFs) specified in 3.5 of Eurocode 8 (EN 1998-3 2005). Conversely, for new materials, nominal properties shall be used without modification by confidence factor. The code also states that in case the structural system, comprising both existing and new structural elements, can be made to fulfill the requirements of EN1998-1-2004, the verifications may be carried out in accordance with the provisions therein. 

The reliability of the results obtained in the previous section can be considered within the framework set out in the EC 8 (CEN 2005), whereby the reliability associated to the results of a seismic assessment of a structure is expressed as a function of the level of knowledge and quantified by means of the confidence factor. Hence this can be considered a measure of the epistemic uncertainty. EC 8 (CEN 2005) recognizes three levels of knowledge (limited, normal, and full) and three fields of knowledge (geometry, construction details, and materials). As data used in the FaMIVE approach are collected by on-site visual inspection with some measurement and in situ accurate observation of construction details, while only very limited in situ nondestructive test on materials are performed and material characteristics are otherwise assigned based on literature or surveyor experience, then the level of knowledge is... 

In Fig. 9 the cumulative distribution for drift at the structural damage state threshold is compared with the curve obtained assuming a confidence factor of 1.25 in agreement with EC8 knowledge level and with the confidence boundaries computed by FaMIVE according to the procedure outlined above. 

The major limitation of using confidence factors in the way suggested by EC8 is the possible underestimation of the overall capacity of the sample and hence an appropriate representation of epistemic xmcertainty. 

Fig. 9 Cumulative distribution for drift at structural damage threshold comparison with curve obtained for an ECS confidence factor of 1.25 and with FaMIVE confidence boundary...

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