• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.87-93
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• 2008

In this paper, we propose a hierarchical fuzzy based nutrition evaluation system that can analyze the individuals' nutrition status through the inference results generated by each layer. Moreover, a method to minimize the uncertainty of inference in the evaluated nutrition status is discussed. To show the effect of the uncertainty in fuzzy inference, we compared the results of nutrition evaluation with/without the certainty factor of rules on 132 people over the age of 65. From the experimental results, we can see that the evaluation method with the modified certainty factor provides better reliability than that of the general evaluation method without the certainty factor.

• The Journal of Fisheries Business Administration
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• v.40 no.1
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• pp.153-172
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• 2009

Developing foreign fishing ground executed in various uncertainty such as fishing price, oil price, exchange rate. But traditional economic evaluation method, CVP(Cost-Volume-Profit) analysis doesn't consider uncertainty of foreign fishing ground. So we need new approach about economic evaluation that can take into account uncertainty. This study focus on the economic evaluation about experimental survey of tuna fishing grounds in the north pacific ocean by sensitive analysis and simulation. The results of the economic evaluation can be summarized as follows. First, when we take it for granted that the other uncertainty factors except for each fishing price, oil price, and exchange rate are constant. CVP gross sales has positive relation to the increasing rate of oil price, exchange rate(W/$) and negative relation to the increasing rate of fishing price and exchange rate(W/${\yen}$). Second, when we are supposing that fishing price, oil price, and exchange rate are followed. the probability of less than CVP gross sales is A ship(48.87%), B ship(49.64%), C ship(50.55%). Consequently, the economic evaluation by sensitive analysis and simulation is more useful tool than CVP(Cost-Volume-Profit) analysis under uncertainty.

• Journal of Powder Materials
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• v.14 no.6
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• pp.410-414
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• 2007

Carbon contamination from the binder resin is an inherent problem with the metal powder injection molding process. Residual carbon in the W-Cu compacts has a strong impact on the thermal and electric properties. In this study, uncertainty was quantified to evaluate determination of carbon in a W-15%Cu MIM body by the combustition method. For a valid generalization about this evaluation, uncertainty scheme applied even to the repeatability as well as the uncertainty sources of each analyse step and quality appraisal sources. As a result, the concentration of carbon in the W-Cu part were measured as 0.062% with expanded uncertainty of 0.003% at 95% level. This evaluation example may be useful to uncertainty evaluation for other MIM products.

• Analytical Science and Technology
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• v.16 no.3
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• pp.185-190
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• 2003

We applied modified least square method (MLS) and ordinary least square method (OLS) to 1st order equation for the comparison of the uncertainties calculated by these methods. The uncertainty calculated by OLS covered statistically safe interval because it was over-estimated in many cases of measurement and concentration level. But, if the uncertainty of the concentration as a reference value was comparably large (about 5% of the relative standard deviation of random scattering from the regression line and about 7% of relative standard uncertainty of reference values), then uncertainty calculated by OLS was seriously under-estimated at high concentration level. It was revealed that the calculated uncertainty didn't cover statistically safe interval at the stated confidence level. It was found that the method, MLS, described in the previously article would be valid for this calculation of uncertainty.

• Proceedings of the KIEE Conference
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• 2003.07c
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• pp.1782-1784
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• 2003

This paper evaluates the uncertainty to measurement of the power of measuring system used in the performance evaluation of electrical apparatus and introduces the reduction method of the uncertainty.

• Journal of Multimedia Information System
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• v.2 no.3
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• pp.255-262
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• 2015

The modern manufacturing systems and technologies produce products that are more accurate day by day. This can be reached mainly by improvement the manufacturing process with at the same time restricting more and more the quality specifications and reducing the uncertainty in part. The main objective an industry becomes to lower the part's variability, since the less variability - the better is product. One of the part of this task is measuring the object's uncertainty. The main purpose of this study is to understand the application of bootstrap method for uncertainty evaluation. Bootstrap method is a collection of sample re-use techniques designed to estimate standard errors and confidence intervals. In the case study a surface of an automobile engine block - (Top view side) is measured by Coordinate Measuring Machine (CMM) and analyzed for uncertainty using Geometric Least Squares in complex with bootstrap method. The designed experiment is composed by three similar measurements (the same features in unique reference system), but with different points (5, 10, 20) concentration at each level. Then each cloud of points was independently analyzed by means of non-linear Least Squares, after estimated results have been reported. A MatLAB software tool used to generate new samples using bootstrap function. The results of the designed experiment are summarized and show that the bootstrap method provides the possibility to evaluate the uncertainty without repeating the Coordinate Measuring Machine (CMM) measurements many times, i.e. potentially can reduce the measuring time.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.137-137
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• 2022

Evaluating interpolated rainfall uncertainty of hydrological models caused by different interpolation methods for basins where can not fully collect rainfall data are necessary. In this study, the adaptive MCMC method under effects of ILFs was used to analyze the interpolated rainfall uncertainty of the SURR model for Gunnam basin, Korea. Three events were used to calibrate and one event was used to validate the posterior distributions of unknown parameters. In this work, the performance of four ILFs on uncertainty of interpolated rainfall was assessed. The indicators of p_factor (percentage of observed streamflow included in the uncertainty interval) and r_factor (the average width of the uncertainty interval) were used to evaluate the uncertainty of the simulated streamflow. The results showed that the uncertainty bounds illustrated the slight differences from various ILFs. The study confirmed the importance of the likelihood function selection in the application the adaptive Bayesian MCMC method to the uncertainty assessment of the SURR model caused by interpolated rainfall.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.5
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• pp.355-362
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• 2002

There has been relatively a few studies that focused on evaluation of uncertainty for standard methods by which criteria pollutants are analyzed in ambient air. Especially, uncertainty evaluation has not been made yet for sampling and analysis of airborne NO$_2$. Ambient NO$_2$ has been thought to be a major criteria pollutant worldwide because of the potential of ozone formation as well as of its own toxicity. In this study, we tried to assess uncertainties associated with the every step of sampling and of analytical procedure of Griess-Saltzman method. Quality assurance (QA) and quality control (QC) were also emphasized with the uncertainty characterization. The use of Griess-Saltzman method for ambient NO$_2$ analysis showed very uniform daily concentration distribution with the mean of 10.8 ppb and the standard deviation of 1.08ppb during the sampling period. However, seven daily samples collected at the same sampling time and place exhibited highly different concentration distribution. Therefore, we evaluated uncertainties associated with sampling and analysis through the precise application of ISO Guide. Estimates of expanded uncertainties for a total of 62 samples fell in a relatively broad range of 5.17% to 11.85%. On the other hand. the expanded uncertainties were smaller for the high concentration range of greater than 15ppb.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.159-179
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• 1997

Traditionally, the evaluation and selection of suppliers have been a major purchasing function. A growing concern for just in-time purchasing, global sourcing, and long-term partnership between buyers and suppliers makes selecting a righ supplier become more critical decision making process. Consequently, a rigorous and systematic method for evaluation suppliers is a must. However, assessing the values of factors(e.g. qulaity , delivery, and service) selected for evaluating suppliers contains elements of uncertainty. Although several methods have been developed for uncertainty analysis, they may not be proper tools for evaluating suppliers under uncertainty. In this paper, a methodology using a fuzzy-set approach in combination with a multicriterion decision-making (MCDM) technique is developed to use as a tool for evaluating suppliers under uncertainty. An numerical example is presented to demonstrate the method in practice.

• Journal of Power System Engineering
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• v.4 no.3
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• pp.72-80
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identification. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identification are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identity the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.