• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.77-90
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• 2003

This paper explores the way and the extent to which drivers' route choice was influenced by uncertain information. In particular, this paper investigates the effect of qualitative information on route choice when drivers face a choice with different degrees of uncertain information. The SP survey was conducted and route choice legit models were estimated. We also applied Prospect Theory to the analysis of drivers' decision making under uncertain information. The main findings are firstly, drivers tend to prefer a route with information than(to) one without information. This indicated that providing charge information encouraged drivers to choose the routes for which information is provided in preference to those for which it is not provided. Secondly, drivers also prefer a route with a certain and precise information over one with uncertain and imprecise information. Thirdly, when the information is given as a range, the size of the range of the information influenced route choice slightly and as the range of the charge increases, the route becomes slightly less unattractive. Fourthly, when the information is given as a range, drivers' route choices are influenced more by the median value of the ranges than by the size of the overall ranges of the information. Application of Prospect Theory to the results explains the way drivers may be interpreting the choice situation and how they make a route choice in response to uncertain information. The results of this paper implicate that drivers' decision making under uncertainty seem to be very complicated and flexible, depending on the way drivers interpret the choice situation. Therefore, it is recommended to apply wider related theories to the analysis of the drivers' behaviour.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.996-1000
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• 2010

본 연구에서는 장기유역모형인 SWAT 모형의 국내 적용의 한계를 인식하여 유출해석모듈과 하도수질모듈 등을 개선한 SWAT-K(Korea) 모형을 통해 수질 모형을 사용하는 의사 결정에 있어 하도추적법이 미치는 영향을 분석하고자 현재 우리나라에서 시행중인 오염총량관리제 개념에 적용하였다. 기준 유량 개념을 도입하여 모의된 수질항목을 평가하기 위하여 장기간의 유황곡선을 작성하고 유황곡선의 초과확률분포를 기준으로 오염부하곡선을 작성하여 하도추적법의 변화가 수질 모의에 미치는 영향을 분석하였다. 또한 이를 바탕으로 수질항목 초과확률분포에 따른 오염부하곡선을 작성하여 모형의 선택에 따라 동일 기준유량시 모의되는 부하량 값의 변화를 분석하였다. 분석 결과 수질 항목은 유황의 변화를 매우 유사하게 재현하며, 수질 매개변수 보정에도 불구하고 하도추적법이 수질 항목의 모의에 있어 매우 중요한 요소임을 확인할 수 있었다. 따라서 본 모형은 정교한 유출 모의와 더불어 오염물질의 신뢰도 높은 모의를 통해 향후 수질오염총량관리제 시행에 기여할 수 있을 것으로 판단된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.2081-2091
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• 2013

Recently, the demand on the practical application of life-cycle cost effectiveness for design and rehabilitation of civil infrastructure is rapidly growing unprecedently in civil engineering practice. Accordingly, in the 21st century, it is almost obvious that life-cycle cost together with value engineering will become a new paradigm for all engineering decision problems in practice. However, in spite of impressive progress in the researches on the LCC, the most researches have only focused on the Deterministic or Probabilistic LCC analysis approach and general bridge at design stage. Thus, the goal of this study is to develop a practical and realistic methodology for the Life-Cycle Cost LCC-effective optimum decision-making based on reliability analysis of bridges at design stage. The proposed updated methodology is based on the concept of Life Cycle Performance(LCP) which is expressed as the sum of present value of expected direct/indirect maintenance costs with expected optimal maintenance scenario. The updated LCC methodology proposed in this study is applied to the optimum design problem of an actual highway bridge with Cable Stayed Bridges. In conclusion, based on the application of the proposed methods to an actual example bridge, it is demonstrated that a updated methodology for performance-based LCC analysis proposed in this thesis, shown applicably in practice as a efficient, practical, process LCC analysis method at design stage.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.89-89
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• 2016

전 세계적으로 발생하는 기후변화로 인해 홍수, 가뭄 등과 같은 자연재해의 빈도가 높아지고 있다. 이러한 자연재해는 사회 경제적으로도 많은 피해를 유발하고 있으며, 특히 물과 관련한 자연재해는 인류의 생존과 직결되는 문제가 된다. 이중에서도 가뭄과 관련한 연구는 진행 속도가 느리고, 가뭄의 진원지나 그 경로를 파악하기 어려운 문제로 인하여 다른 연구와 비교하였을 때 상대적으로 미흡하게 진행되어 왔다. 이러한 문제점 때문에 여타의 다른 자연재해에 비해 가뭄에 대한 예측 및 대책 마련 또한 쉽지 않은 실정이다. 이에 몬테카를로 모의를 통해 미래에 발생할 수 있는 다양한 시나리오를 도출하는 확률론적 접근을 통해 좀 더 효율적이고 현실적인 대책 안을 마련할 수 있다. 본 연구의 목표는 기존 강우생성기와 증발산생성기를 결합한 일기생성기를 개발하고 이를 기후변화 시나리오에 적용하여 미래의 가뭄위험지수를 산출하는 것이다. 산출된 결과를 토대로 우리나라 전역에 대하여 준 실시간으로 갱신되는 미래가뭄위험도의 지도를 제작할 수 있다. 본 연구의 차별성은 첫 번째로 추계론적 접근을 통해 현재의 가뭄상태에 근거한 미래 가뭄에 대한 위험도를 예측할 수 있음을 들 수 있으며, 두 번째로는 지표해석모형을 활용하여 가뭄을 해석하기 때문에 유역 전반에 걸친 토양수분 뿐 만 아니라 국내 주요 댐 상류의 저수지 유입량의 불확실성을 정량화 할 수 있으며, 이는 기후변화에 따른 수자원 장기계획의 수립 및 의사결정에 있어 실용적인 정보를 제공할 수 있다.

• Korean Journal of Construction Engineering and Management
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• v.8 no.5
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• pp.71-79
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• 2007

It is common that the analysis of VE/LCC is performed in design phase of quay wall structures. The analysis is mainly executed based on experience and engineering sense of expert considering the selection of construction method, construction and maintenance cost. Recently there are increasing demands on the analysis that includes uncertainty and vulnerability of input parameters, for this purpose, fuzzy reliability based probabilistic VE/LCC analysis model for quay wall structures is suggested. In VE/LCC analysis for quay wall structures, the application of probabilistic analysis method give very similar results compare with those of deterministic analysis method. It is anticipated that the methodology proposed in this paper can also be utilized in the design and maintenance phase of other facilities where decision making is made for the probabilistic life cycle cost and value analysis.

• Journal of Korea Water Resources Association
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• v.32 no.1
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• pp.3-13
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• 1999

In this study, an alternative spatial analysis method against conventional methods such as Thiessen method, Inverse Distance method, and Kriging method, named Spatial-Analysis Neural-Network (SANN) is presented. It is based on neural network modeling and provides a nonparametric mean estimator and also estimators of high order statistics such as standard deviation and skewness. In addition, it provides a decision-making tool including an estimator of posterior probability that a spatial variable at a given point will belong to various classes representing the severity of the problem of interest and a Bayesian classifier to define the boundaries of subregions belonging to the classes. In this paper, the SANN is implemented to be used for analyzing a mean annual precipitation filed and classifying the field into dry, normal, and wet subregions. For an example, the whole area of South Korea with 39 precipitation sites is applied. Then, several useful results related with the spatial variability of mean annual precipitation on South Korea were obtained such as interpolated field, standard deviation field, and probability maps. In addition, the whole South Korea was classified with dry, normal, and wet regions.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.501-501
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• 2015

댐과 같은 수공구조물의 치수능력부족은 구조물의 파손이나 붕괴로 직결되며, 대규모 재산피해와 인명피해가 불가피하다. 또한 최근 기후변화 현상에 의해 발생되고 있는 예상치 못한 큰 강우와 홍수는 댐 안전을 저하하는 요소로 간주되며, 복합적으로 발생시 댐의 치수능력이 크게 저하되어 댐 파괴에 영향을 미칠 가능성이 크다. 또한 ICOLD, 세계대댐회 등의 조사 결과 댐 파괴에 큰 영향을 미치고 있는 수문학적 요소로서 예상치 못한 강우, 홍수 및 월류로 조사되었다. 이러한 이유로 수문학적 위험인자를 효과적으로 고려하기 위해 2000년도 이후 선진국에서는 위험도 해석 기법을 기반으로 파괴모드, 다양한 하중조건 등을 조합하여 위험도 해석을 통해 댐의 안전도 검토를 실시하고 있다. 따라서 최근 증가하는 기상변동성을 능동적으로 고려하기 위해서는 위험도 해석기반의 수공구조물 안정성 평가기법을 기반으로 하는 종합적인 위험도 해석 방안수립이 요구된다. 이러한 이유로 본 연구에서는 BN 모형 기반의 댐 위험도 적용에 앞서 실증댐을 대상으로 분석을 수행하였으며, 분석 절차는 다음과 같다. 첫째, ICOLD 및 세계대댐회 등 다양한 논문, 보고서 등을 조사하여 댐 붕괴에 가장 큰 영향을 미치는 수문학적 파괴인자를 도출하였다. 둘째, BN 모형 구축시 각 노드는 앞서 도출된 수문학적 파괴인자를 이용하였으며, 각 파괴인자에 적합한 확률분포형을 부여하였다. 마지막으로, 노드별 임계값을 부여하여 상황별 파괴인자의 변화 양상을 도출하였다. 본 연구의 결과로 인해 연구대상댐의 가장 취약한 수문학적 파괴인자 도출이 가능하며, 댐의 보수 보강시 우선순위 의사결정의 지원이 가능 할 것으로 판단된다.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.195-204
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• 2008

Multi-Criteria Analysis is one method for optimizing decisions that include numerous characteristics and objective functions. The Analytic Hierarchy Process (AHP) is used as a general Multi-Criteria Analysis considering many critical issues. However, since validation procedures for the decision reliability of AHP valuers had been left off existing methodologies, a new methodology including such validation procedures is required to make more reliable decisions. In this research, idea decision results are derived using Monte Carlo Simulation in cases where AHP valuers do not have expertise in the specific project, and these results are compared with the results derived from experts to develop a new analysis model to make more reliable decisions. Finally, this new analysis is applied to various field case studies of road and rail carried out by the Korea Development Institute (KDI) between 2003 and 2006 to validate the new analysis model. The study found that approximately 20% of decisions resulting from the existing methodology are considered prudent. In future studies, the authors suggest analyzing the correlation between initial weights and final results since final results are enormously influenced by the initial weight.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.114-125
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• 2009

In this study, a design value analysis technique that considered stochastic LCC and stochastic performance evaluation was proposed, and by introducing the concept of reliability analysis, a decision making that secured reliability was supported. The results of this study, which was carried out according to the above objectives and methods, are summarized as follows: 1) The design value analysis procedures and value state function, improved in order to carry out a reliable analysis when evaluating alternate proposals that were extracted after the function definition was complete, were formalized, and in order to secure consistency and efficiency for value evaluation procedures, an evaluation index scheme was proposed; 2) Database collection and analysis were done for a bridge's LCC analysis. As for the collection scope of data, literature of previous research done on a bridge's LCC analysis was used as the basis for analysis, and for securing reliability regarding analysis results and dealing with uncertainty of collected data, the MCS technique was applied; 3) Weights and evaluation ranks for performance evaluation of each of the alternate proposals, as well as LCC analysis model, analysis period, discount rate, user expense, safety inspection and safety diagnosis expense conditions for LCC analysis were proposed. Lastly, a feasibility study was done and conclusion was made about "OO grand bridge and connecting road construction work execution design" project centered on value analysis execution case.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.817-830
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• 2015

This study performed prediction of extreme rainfall uncertainty and its frequency analysis based on climate change scenarios by Coupled Model Intercomparison Project Phase 5 (CMIP5) for the selected nine-General Circulation Models (GCMs) in the near future (2011-2040) over the Korean Peninsula (KP). We analysed uncertainty of scenarios by multiple model ensemble (MME) technique using non-parametric quantile mapping method and bias correction method in the basin scale of the KP. During the near future, the extreme rainfall shows a significant gradually increasing tendency with the annual variability and uncertainty of extreme ainfall in the RCP4.5, and RCP8.5 scenarios. In addition to the probability rainfall frequency (such as 50 and 100-year return periods) has increased by 4.2% to 10.9% during the near future in 2040. Therefore, in the longer-term water resources master plan, based on the various climate change scenarios (such as CMIP5 GCMs) and its uncertainty can be considered for utilizing of the support tool for decision-makers in water-related disasters management.