• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.373-373
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• 2012

위험도(risk)는 복잡성(complexity)과 불확실성(uncertainty)라는 2가지 주요 특징으로 인해 위험도를 정확하게 예측하는 것은 불가능하다. 대표적인 수공구조물인 댐이 각종 모니터링을 통해서 안전하다고 판단된다 하더라도 하류지역에 도시가 존재한다면 여전히 잔존위험도(residual risk)는 존재한다. 댐의 파괴가 일반적으로 발생하는 사상은 아니지만 대규모 인명피해, 재산 및 환경피해로 이어지기 때문에 작은 위험도라 할지라도 이에 대한 감시 및 관리가 필수적이다. 댐 위험도 분석을 위해서 Event Tree 또는 Fault Tree가 일반적인 해석 방법으로 이용되고 있으나 잠재적인 파괴모드에 대한 복잡성과 불확실성을 고려하는데 한계가 존재한다. 본 연구에서는 이러한 문제점을 개선하기 위해서 Bayesian Network 기반의 위험도 해석기법을 제안하고자 한다. 특히 수문학적 위험도와 관련된 분석을 위해서 Bayesian Network의 구성 방안, 매개변수 추정, 위험도 해석 등 기존 해석 방법을 개선한 댐 위험도 해석 기법을 개발하고자 하며 개발된 방법론을 국내 실제댐에 적용하여 적합성을 평가하였다.

• Journal of Environmental Impact Assessment
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• v.5 no.1
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• pp.47-60
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• 1996

Nitrate contamination problems from groundwater supplies have been reported throughout many countries in the world, including Korea. Nitrate salts can induce methemoglobinemia and possibly human gastric cancer. To reduce human health risk from nitrate in groundwater supplies, several nitrate risk-management strategies can be developed based on the acceptable level of human health risk, the reasonableness of nitrate-control cost, and the technical feasibility of nitrate-control methods. However, due to a lack of available information, assessing risk, cost and technical feasibility contains elements of uncertainty. In the present paper, a nitrate risk-management methodology using fuzzy sets in combination with a multiobjective decision-making (MODM) technique is developed to assist decision makers in evaluating, with uncertain information, various nitrate risk-management strategies in order to decide a proper strategy.

• Journal of Environmental Policy
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• v.7 no.4
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• pp.57-73
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• 2008

This short paper considers the situation where an environmental policy could play a source of an exogenous background risk at an individual's wealth and analyzes the effect of such a background risk on the individual's decision making in a simple chance-improving model. Our analysis shows that risks at initial wealth generated by an environmental policy could be regarded as an exogenous background risk in many cases and that such a risk makes a risk averse person behave more risk aversely in some restricted decision making situations. A policy maker considering an environmental policy which would affect individuals' initial wealth should take into account that the environmental policy could affect an individual's seemingly irrelevant economics decisions via his or her wealth.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.62-70
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• 2013

This study proposes smart-phone game applications success model based on mobile internet success model and investigates the effects of cultural propensities especially, uncertainty avoidance and power distance at the individual level. To achieve our research purposes, the study conducted survey in Korea and a total of 221 people participated in the survey. We classified user types by cultural difference as a moderating variable. User's cultural propensity classified two groups: high uncertainty avoidance and high power distance, low uncertainty avoidance and low power distance. This study results reveal that the impact of quality factors on user satisfaction have difference according to cultural propensities.

• Smart Media Journal
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• v.11 no.9
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• pp.9-20
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• 2022

Deep reinforcement learning(RL) is an end-to-end data-driven control method that is widely used in the autonomous driving domain. However, conventional RL approaches have difficulties in applying it to autonomous driving tasks due to problems such as inefficiency, instability, and uncertainty. These issues play an important role in the autonomous driving domain. Although recent studies have attempted to solve these problems, they are computationally expensive and rely on special assumptions. In this paper, we propose a new algorithm MCDT that considers inefficiency, instability, and uncertainty by introducing a method called uncertainty sequence modeling to autonomous driving domain. The sequence modeling method, which views reinforcement learning as a decision making generation problem to obtain high rewards, avoids the disadvantages of exiting studies and guarantees efficiency, stability and also considers safety by integrating uncertainty estimation techniques. The proposed method was tested in the OpenAI Gym CarRacing environment, and the experimental results show that the MCDT algorithm provides efficient, stable and safe performance compared to the existing reinforcement learning method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.7
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• pp.921-927
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• 2013

The performance estimation of a landing gear with uncertain parameters is presented. In actual use, many parameters can have certain degrees of variations that affect the energy absorbing performance. For example, the shock strut gas pressure, oil volume, tire pressure, and temperature can deviate from their nominal values. The objective function in this study is the ground reaction during touchdown, which is a function of the abovementioned parameters and time. To consider the uncertain properties, convex modeling and interval analysis are used to calculatethe objective function. The numerical results show that the ground reaction characteristics are quite different from those of the deterministic method. The peak load, which affects the efficiency and structural integrity, is increases considerably when the uncertainties are considered. Therefore, it is important to consider the uncertainties, and the proposed methodology can serve as an efficient method to estimate the effect of such uncertainties.

• Environmental and Resource Economics Review
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• v.26 no.3
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• pp.359-398
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• 2017

Uncertainty is central to energy and climate policy. A growing number of literature show that almost all components of energy and climate models are, to some extent, uncertain and that the effect of uncertainty on the model outputs, in turn policy recommendations, is significantly large. Most existing energy and climate-economy models developed and used in Korea, however, do not take uncertainty into account explicitly. Rather, many models conduct a deterministic analysis or do a simple (limited) sensitivity analysis. In order to help social planners to make more robust decisions (across various plausible situations) on energy and climate change issues, an uncertainty analysis should be conducted. As a first step, this paper reviews the theory of decision making under uncertainty and the method for addressing uncertainty of existing probabilistic energy and climate-economy models. In addition, the paper proposes a strategy to apply an uncertainty analysis to energy and climate-economy models used in Korea. Applying the uncertainty analysis techniques, this paper revises the FUND model and investigates the impacts of climate change in Korea.

• Electronics and Telecommunications Trends
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• v.29 no.5
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• pp.72-85
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• 2014

현대 산업사회는 시장의 불확실성과 기술의 불확실성이 공존하면서, 글로벌 경제의 저성장에 대한 우려, 불확실성의 증대가 더욱 크게 산업 전반의 스트레스로 작용하고 있다. 이는 R&D-생산-마케팅 자원의 낭비를 초래하게 되고, 시대/경제/산업의 변화는 더욱 이러한 환경을 가속화시키고 있다. 에너지 분야에서도 환경 위기, 지속가능 에너지, 화석연료 고갈, 기후변화 등의 당면 문제를 해결하지 못한다면, 인류 공멸의 위기에 직면할 것이다. 정부에서는 창조경제의 주요 아젠다로 에너지 분야의 다양한 정책과 기술개발을 드라이브하고 있으며, 에너지 ICT 융합을 통해 이를 실현하고자 하고 있다. 본고에서는 에너지 ICT 기술의 개발동향과 발전방향 및 트렌드를 분석해 보고, 현재 진행 중인 국내(ETRI)의 기술개발 사례를 소개하고자 한다.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.135-146
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• 2022

A safe working environment is an important and crucial factor in the operation of a firm, and is also essential for logistics companies in supply chain management. This study confirmed that the safety climate and safety prevention activities have a positive relationship with safety behavior from the perspective of domestic small and medium-sized logistics companies that continue their business relationships by signing contracts with large logistics companies. In addition, the moderating role of regulatory uncertainty and competition uncertainty in the previous positive relationship was empirically examined.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1099-1108
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• 2017

Data points obtained by conducting repetitive experiments under identical environmental conditions are, theoretically, required to correspond. However, experimental data often display variations due to generated errors or noise resulting from various factors and inherent uncertainties. In this study, an algorithm aiming to determine valid bounds of input variables, representing uncertainties, was developed using probabilistic and statistical methods. Furthermore, a reliability assessment was performed to verify and validate applications of this algorithm using bolt-fastening friction coefficient data in a sample application.