• 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 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.

• International Journal of Contents
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• v.8 no.1
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• pp.100-107
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• 2012

While considerable research suggests that users' uncertainty gradually decreases, as they proceed through the information seeking process, others argue that it can arise at any stage of their information seeking process. Reflecting the latter view, this study examined user perceptions of uncertainty in the final stage of users' information seeking process, the stage of search results evaluation. Considering the significance of Web search engines for academic study, this study investigated the relevance decision stage of scholarly researchers in the field of science, who use Web search engines for their academic study. Based on the analysis of the users' uncertainty, this study provided implications to improve information systems and Web contents design.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.311-322
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• 1999

Major problems involved in an electrical utility expansion planning within a time horizon are how to efficiently deal with objectives considering multiple factors and uncertainty. But justification factors in study these days have considered only quantitative factors except qualitative factors. Therefore, the purpose of this paper is to develop a new model for economic evaluation of nuclear power plants through the scoring model with the quantitative and qualitative factors under uncertainty. The quantitative factors use a levelized generation cost method considering time value of money. Especially, the environmental, risk, and safety factors in this paper have been also explained for the rational economic justification of the qualitative factors under uncertainty. This paper not only proposes a new approach method using the scoring model in evaluating economy of the nuclear power plant in the long term, but also provides the more efficient decision making criterion for nuclear power plants under uncertainty.

• 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 KSR Conference
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• 2003.10c
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• pp.301-306
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• 2003

Recently, uncertainty of measurement became a major concern for the people working on the laboratory evaluation and accreditation. 'uncertainty of measurement is a parameter associated with the result of a measurement that characteristics the dispersion of the value that could reasonably be attributed to the measured.' This study analysed how to estimate uncertainty of measurement in mechanical characteristic exam for Plastic material. its uncertainty was estimated according to International Organization for Standardization(ISO), they were named to A type uncertainty, B type uncertainty, combined standard uncertainty, and expanded uncertainty. We obtained that the combined standard uncertainty was 0.96697 MPa and the expanded uncertainty was 2.291MPa.

• Journal of Climate Change Research
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• v.7 no.4
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• pp.407-419
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• 2016

The low flow is the necessary and important index to establish national water planning, however there are lots of uncertainty in the low flow estimation. Therefore, the objectives of this study are to assess the climate change uncertainty and the effects of hydrological models on low flow estimation. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods and 2 hydrological models were applied for evaluation. The study area were selected as Chungju dam and Soyang river dam basin, and the 30 days minimum flow is used for the low flow evaluation. The results of the uncertainty analysis showed that the hydrological model was the largest source of uncertainty about 41.5% in the low flow projection. The uncertainty of hydrological model is higher than the other steps (RCM, statistical post-processing). Also, VIC model is more sensitive for climate change compared to SWAT model. Therefore, the hydrological model should be thoroughly reviewed for the climate change impact assessment on low flow.

• Bulletin of the Korean Chemical Society
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• v.22 no.3
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• pp.251-252
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• 2001

• 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.