• 한국환경과학회:학술대회논문집
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• 한국환경과학회 2007년도 춘계 학술발표회 발표논문집
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• pp.199-202
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• 2007

• 한국소음진동공학회논문집
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• 제21권11호
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• pp.1051-1058
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• 2011

The military communication equipment is required the high reliability for operating adequate functions under severe conditions. This reliability is the essential element for the quality of the product, for the uncontrolled factors, such as the clearance, damage of the material, the reduction of stiffness, which are the designer is unable to handle. In this paper, the uncertainty for the dimension was supposed to the probability model for the military communication equipment, and the average of the objective function was minimized for reducing design uncertainty. The reliability-based design optimization which was implemented the limit state function was formulated into the mathematical model, so the reliable optimized structure was implemented than the base-line design.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 추계학술대회 논문집
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• pp.504-509
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• 2011

The military communication equipment is required the high reliability for operating adequate functions under severe conditions. This reliability is the essential element for the quality of the product, for the uncontrolled factors, such as the clearance, damage of the material, the reduction of stiffness, which are the designer is unable to handle. In this paper, the uncertainty for the design was supposed to the probability model for the military communication equipment, and the average of the objective function was minimized for reducing design uncertainty. The reliability-based design optimization which was implemented the limit state function was formulated into the mathematical model, so the reliable optimized structure was implemented than the base-line design.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2004년도 학술발표회
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• pp.1285-1289
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• 2004

Elman Discrete Recurrent Neural Networks Model(EDRNNM) was used to be a suitable short-term hydrological forecasting tool yielding a very high degree of flood stage forecasting accuracy at Musung station of Wi-stream one of IHP representative basins in South Korea. A relative new approach method has recurrent feedback nodes and virtual small memory in the structure. EDRNNM was trained by using two algorithms, namely, LMBP and RBP The model parameters, optimal connection weights and biases, were estimated during training procedure. They were applied to evaluate model validation. Sensitivity analysis test was also performed to account for the uncertainty of input nodes information. The sensitivity analysis approach could suggest a reduction of one from five initially chosen input nodes. Because the uncertainty of input nodes information always result in uncertainty in model results, it can help to reduce the uncertainty of EDRNNM application and management in small catchment.

• 유통과학연구
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• 제13권5호
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• pp.71-82
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• 2015

Purpose - The purpose of this study is to investigate risk price implied from the pricing kernel of Korean stock distribution market. Recently, it is considered that the quantitative easing programs of major developed countries are contributing to a reduction in global uncertainty caused by the 2007~2009 financial crisis. If true, the risk premium as compensation for global systemic risk or economic uncertainty should show a decrease. We examine whether the risk price in the Korean stock distribution market has declined in recent years, and attempt to provide practical implications for investors to manage their portfolios more efficiently, as well as academic implications. Research design, data and methodology - To estimate the risk price, we adopt a non-parametric method; the minimum norm pricing kernel method under the LOP (Law of One Price) constraint. For the estimation, we use 17 industry sorted portfolios provided by the KRX (Korea Exchange). Additionally, the monthly returns of the 17 industry sorted portfolios, from July 2000 to June 2014, are utilized as data samples. We set 120 months (10 years) as the estimation window, and estimate the risk prices from July 2010 to June 2014 by month. Moreover, we analyze correlation between any of the two industry portfolios within the 17 industry portfolios to suggest further economic implications of the risk price we estimate. Results - According to our results, the risk price in the Korean stock distribution market shows a decline over the period of July 2010 to June 2014 with statistical significance. During the period of the declining risk price, the average correlation level between any of the two industry portfolios also shows a decrease, whereas the standard deviation of the average correlation shows an increase. The results imply that the amount of systematic risk in the Korea stock distribution market has decreased, whereas the amount of industry-specific risk has increased. It is one of the well known empirical results that correlation and uncertainty are positively correlated, therefore, the declining correlation may be the result of decreased global economic uncertainty. Meanwhile, less asset correlation enables investors to build portfolios with less systematic risk, therefore the investors require lower risk premiums for the efficient portfolio, resulting in the declining risk price. Conclusions - Our results may provide evidence of reduction in global systemic risk or economic uncertainty in the Korean stock distribution market. However, to defend the argument, further analysis should be done. For instance, the change of global uncertainty could be measured with funding costs in the global money market; subsequently, the relation between global uncertainty and the price of risk might be directly observable. In addition, as time goes by, observations of the risk price could be extended, enabling us to confirm the relation between the global uncertainty and the effect of quantitative easing. These topics are beyond our scope here, therefore we reserve them for future research.

• Wind and Structures
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• 제22권1호
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• pp.17-41
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• 2016

To address the uncertainty of the flight trajectories caused by the turbulence and gustiness of the wind field over the roof and in the wake of a building, a 3-D probabilistic trajectory model of flat-type wind-borne debris is developed in this study. The core of this methodology is a 6 degree-of-freedom deterministic model, derived from the governing equations of motion of the debris, and a Monte Carlo simulation engine used to account for the uncertainty resulting from vertical and lateral gust wind velocity components. The influence of several parameters, including initial wind speed, time step, gust sampling frequency, number of Monte Carlo simulations, and the extreme gust factor, on the accuracy of the proposed model is examined. For the purpose of validation and calibration, the simulated results from the 3-D probabilistic trajectory model are compared against the available wind tunnel test data. Results show that the maximum relative error between the simulated and wind tunnel test results of the average longitudinal position is about 20%, implying that the probabilistic model provides a reliable and effective means to predict the 3-D flight of the plate-type wind-borne debris.

• 환경정책연구
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• 제5권3호
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• pp.57-78
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• 2006

2013년 이후의 온실가스 의무저감에 대한 참여국 및 배출목표에 대한 논의가 진행중인 지금, 5년 단위의 단기 접근방식과는 별도로 2050년 장기 온실가스 저감 시나리오에 대한 연구가 유럽 국가들을 중심으로 활발히 진행 중이다. 본 논문에서는 영국, 독일, 프랑스, 네덜란드 등 유럽 국가들의 2050년 장기 온실가스 저감 시나리오 수립의 배경, 온도 목표, $CO_2$ 농도 목표, 국가 배출량 목표, 접근방식 등을 중점적으로 검토하였다. 그리고 선진국들과 우리나라의 경제활동 및 배출량 관련한 지표들을 비교하고, 우리나라의 장기 온실가스 저감 시나리오 수립에 갖는 시사점을 살펴보았다. 기후 변화의 과학적 불확실성으로 인하여 온실가스 저감활동을 지연하기보다는, 기후변화의 영향과 기술개발의 불확실성 역시 고려하여 저감활동을 일찍부터 장려할 필요가 있으며, 2050년 장기 저감목표의 설정을 통하여 기후변화 대응에 대한 우리 사회의 비전과 정부정책 방향을 경제주체들에게 분명히 제시하고, 이에 대비할 수 있도록 할 필요가 있다.

• Journal of Power Electronics
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• 제4권1호
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• pp.1-11
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• 2004

A stable adaptive sensorless speed controller for three-level inverter fed induction motor direct torque control (DTC) system using the radial-basis function network (RBFN) is presented in this paper. Torque ripple in the DTC system for high power induction motor could be drastically reduced with the foregoing researches of switching voltage selection and torque ripple reduction algorithms. However, speed control performance is still influenced by the inherent uncertainty of the system such as parametric uncertainty, external load disturbances and unmodeled dynamics, and its exact mathematical model is much difficult to be obtained due to their strong nonlinearity. In this paper, the inherent uncertainty is approximated on-line by the RBFN, and an additional robust control term is introduced to compensate for the reconstruction error of the RBFN instead of the rich number of rules and additional updated parameters. Control law for stabilizing the system and adaptive laws for updating both of weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov, and the stability proof of the whole control system is presented. Computer simulations as well as experimental results are presented to show the validity and effectiveness of the proposed system.

• Earthquakes and Structures
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• 제8권4호
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.

• 한국가시화정보학회지
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• 제17권2호
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• pp.48-57
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• 2019

A straightforward strategy for particle image velocimetry (PIV) interrogation and post-processing has been proposed, aiming at reducing errors and clarifying vortex structures. The interrogation window size should be kept small to reduce bias error and improve spatial resolution. A spatial filter is then applied to the velocity field to reduce random error and clarify flow structure. The performance of three popular spatial filters were assessed: box filter, median filter, and local quadratic polynomial regression filter. In order to quantify random uncertainty, the image matching (IM) method is applied to an experimental dataset of homogeneous and isotropic turbulence (HIT) obtained by 2D-PIV. We statistically analyze the uncertainty propagation through the spatial filters, and verify the reduction in random uncertainty. Moreover, we illustrate that the spatial filters help clarify vortex structures using vortex identification criteria. As a result, PIV random uncertainty was reduced and the vortex structures became clearer by spatial filtering.