• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.179-185
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• 2010

In a sensitivity analysis, an uncertainty importance measure is often used to assess how much uncertainty of an output is attributable to the uncertainty of an input, and thus, to identify those inputs whose uncertainties need to be reduced to effectively reduce the uncertainty of output. A function is called monotonic if the output is either increasing or decreasing with respect to any of the inputs. In this paper, for a monotonic function, we propose a method for evaluating the measure which assesses the expected percentage reduction in the variance of output due to ascertaining the value of input. The proposed method can be applied to the case that the output is expressed as linear and nonlinear monotonic functions of inputs, and that the input follows symmetric and asymmetric distributions. In addition, the proposed method provides a stable uncertainty importance of each input by discretizing the distribution of input to the discrete distribution. However, the proposed method is computationally demanding since it is based on Monte Carlo simulation.

• Journal of the Korean Geotechnical Society
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• v.28 no.1
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• pp.17-27
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• 2012

Since geologic data are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations but also to assess the uncertainty attached to the prediction. In this study the assessment of the local uncertainty of prediction for the thickness of the consolidation layer was performed by using the indicator approach. A conditional cumulative distribution function (ccdf) was first modeled, and then E-type estimates and the conditional variance were computed for the spatial distribution of the thickness of the consolidation layer. These results could be used to estimate the spatial distribution of secondary compression and to assess the local uncertainty of secondary compression for Songdo New City.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.95-106
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• 2013

It is now generally known that dynamical climate modeling outputs include systematic biases in reproducing the properties of atmospheric variables such as, preciptation and temerature. There is thus, general consensus among the researchers about the need of bias-correction process prior to using climate model results especially for hydrologic applications. Among the number of bias-correction methods, distribution (e.g., cumulative distribution fuction, CDF) mapping based approach has been evaluated as one of the skillful techniques. This study investigates the uncertainty of using various CDF mapping-based methods for bias-correciton in assessing regional climate change Impacts. Two different dynamicailly-downscaled Global Circulation Model results (CCSM and GFDL under ARES4 A2 scenario) using Regional Spectial Model for retrospective peiod (1969-2000) and future period (2039-2069) were collected over the west central Florida. Total 12 possible methods (i.e., 3 for developing distribution by each of 4 for estimating biases in future projections) were examined and the variations among the results using different methods were evaluated in various ways. The results for daily temperature showed that while mean and standard deviation of Tmax and Tmin has relatively small variation among the bias-correction methods, monthly maximum values showed as significant variation (~2'C) as the mean differences between the retrospective simulations and future projections. The accuracy of raw preciptiation predictions was much worse than temerature and bias-corrected results appreared to be more significantly influenced by the methodologies. Furthermore the uncertainty of bias-correction was found to be relevant to the performance of climate model (i.e., CCSM results which showed relatively worse accuracy showed larger variation among the bias-correction methods). Concludingly bias-correction methodology is an important sourse of uncertainty among other processes that may be required for cliamte change impact assessment. This study underscores the need to carefully select a bias-correction method and that the approach for any given analysis should depend on the research question being asked.

• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.176-182
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• 2012

This paper presents a new approach to risk comparison in uncertain environment. Based on the uncertainty theory, some uncertain risk measures and risk comparison rules are proposed. Afterward the bridges are built between uncertain risk measures and risk comparison rules. Finally, several comparable examples are given.

• Journal of Applied Reliability
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• v.3 no.1
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• pp.83-92
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• 2003

We studied the trend change of failure rate function and uncertainty of residual life function in terms of location of their trend change points. It is shown that the trend change of uncertainty of residual life takes place before the failure rate changes its trend. Like DIFR(IDFR) does not necessary implies IDMRL(DIMRL), we find the fact that DIFR(IDFR) does not always imply IDURL(DIURL) under certain conditions, through the exponentiated-weibull distribution.

• Journal of Distribution Research
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• v.4 no.1
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• pp.71-92
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• 1999

The basic purpose of this study is to investigate how the traits of the buyer-seller transaction-relationship relate to relationship performance, including relationship performance explicitly in the proposed model. The traits examined include relational norm, formalization, market uncertainty, and relationship investment. It is hypothesized that relational norm and formalization have positive impacts on relationships performance while market uncertainty has a minus impact. In addition, it is hypothesized that relational norm has a positive moderating impact on the effect of relationship investment--the investment and efforts for maintaining a relationship to relationship performance. A mail-survey to the manufacturers of machinery and equipment about their relationships with the parts suppliers was performed. Data provided a strong support for the hypotheses. As hypothesized, relationship performance and formalization generally had positive impacts on relationship performance and formalization generally had positive impacts on relationship performance while market uncertainty showed negative impacts. Also, there is a good evidence for the positive moderating effect of relational norm to the impact of relationship investment on relationship performance.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.325-334
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• 2016

We projected the distribution of Hedera rhombea, an evergreen broad-leaved climbing plant, under current climate conditions and predicted its future distributions under global warming. Inaddition, weexplained model uncertainty by employing 9 single Species Distribution model (SDM)s to model the distribution of Hedera rhombea. 9 single SDMs were constructed with 736 presence/absence data and 3 temperature and 3 precipitation data. Uncertainty of each SDM was assessed with TSS (Ture Skill Statistics) and AUC (the Area under the curve) value of ROC (receiver operating characteristic) analyses. To reduce model uncertainty, we combined 9 single SDMs weighted by TSS and resulted in an ensemble forecast, a TSS weighted ensemble. We predicted future distributions of Hedera rhombea under future climate conditions for the period of 2050 (2040~2060), which were estimated with HadGEM2-AO. RF (Random Forest), GBM (Generalized Boosted Model) and TSS weighted ensemble model showed higher prediction accuracies (AUC > 0.95, TSS > 0.80) than other SDMs. Based on the projections of TSS weighted ensemble, potential habitats under current climate conditions showed a discrepancy with actual habitats, especially in the northern distribution limit. The observed northern boundary of Hedera rhombea is Ulsan in the eastern Korean Peninsula, but the projected limit was eastern coast of Gangwon province. Geomorphological conditions and the dispersal limitations mediated by birds, the lack of bird habitats at eastern coast of Gangwon Province, account for such discrepancy. In general, potential habitats of Hedera rhombea expanded under future climate conditions, but the extent of expansions depend on RCP scenarios. Potential Habitat of Hedera rhombea expanded into Jeolla-inland area under RCP 4.5, and into Chungnam and Wonsan under RCP 8.5. Our results would be fundamental information for understanding the potential effects of climate change on the distribution of Hedera rhombea.

• Journal of the Korean Operations Research and Management Science Society
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• v.11 no.1
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• pp.44-50
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• 1986

In this paper, we find optimal policy for the (Q, r) inventory model under the lead time uncertainty. The (Q, r) inventory model is such that the fixed order quantity Q is placed whenever the level of on hand stock reaches the reorder point r. We first develop the single level inventory model as the basis for the analysis multi-level distribution systems. The functional problem is to determine when and how much to order in order to minimize the expected total cost per unit time, which includes the set up, inventory holding and inventory shortage cost. The model, then, is extended to the multi-level distribution system consisting of the factory, warehouses and retailers. In this case, we also find an optimal policy which minimizes the total cost of the contralized multi-level distribution system.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.263-269
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• 2022

The global financial crisis of 2008-2009 and the COVID-19 pandemic that started in 2019 along with the slow and unstable recovery of the global economy have raised concerns about the impact of global uncertainty on the macroeconomics of the countries. The paper used the Structural Vector Autoregression (SVAR) model to examine the impact of global uncertainty shocks on Vietnam's economy from the period 2008-2022. We found that Vietnam's output dropped following the shock of global uncertainty, the peak was in the third month, and lasted for one year. Inflation in Vietnam had a rapid downturn in the first month, peaked in the seventh month, and took a long time to cease. When the economy experienced the shock of increased global uncertainty, Vietnam's policy interest rate was adjusted downward. Additionally, we included a long-term interest rate to consider the overall impact of monetary policy into account. A decreasing trend was also found with this rate. The global uncertainty shock effects acted as the aggregate demand shocks, reducing output and inflation as the uncertainty increases and vice versa, thus monetary policy can be used to regulate Vietnam's economy to deal with negative shocks without the trade-offs between output and inflation as aggregate supply shocks.

• 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.