• 제목/요약/키워드: environmental uncertainties

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수자원 공급 사업의 경제성 평가: 실물옵션가치평가기법의 적용성 검토 (Applicability of the Real Option Valuation Method to the Economic Analysis of Water Resources Supply Projects)

  • 유순영;;김태희
    • 자원환경지질
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    • 제41권5호
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    • pp.551-562
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    • 2008
  • 금융시장에서 옵션과 같은 파생상품의 가격 결정에 이용되는 옵션가격결정모델의 기본개념이 비금융 사업의 옵션가치 평가에 이용되고 있다. 본 논문에서는 실물옵션이라 불리는 이들 비금융 사업 옵션의 특성을 살펴보고, 실물옵션가치평가기법이 수자원 공급 사업의 경제성 평가에 이용되는 방안을 검토해 보고자 하였다. 수자원 공급 사업이 일반적으로 대규모 투자비용이 소요되고, 사업 기간이 긴 이유로 말미암아 경영상의 유연성이 요구되며, 미래의 수익과 비용 흐름이 불확실하다는 것을 고려할 때, 실물옵션가치평가기법은 운영 옵션의 가치를 평가하고, 이를 수자원 공급 사업의 가치 평가 과정에 포함시키므로써, 기존 현금흐름할인법의 단점을 보안할 수 있는 경제적 가치 평가 기법으로 이용될 수 있을 것으로 보인다.

대안 평가를 위한 의사결정 기법 (Decision Methods for Evaluation of Alternatives)

  • 남기창;홍상표
    • 환경영향평가
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    • 제9권4호
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    • pp.363-372
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    • 2000
  • For any particular development project or environmental regulations, decision-making criteria is required and conflicts among criteria should be resolved. It is necessary to investigate criteria that government agencies employ in making decisions that influence the environment. The evaluation of alternative development proposals and regulatory measures involves much more than environmental issues. Economic, technical, and social factors should be considered along with environmental impacts when making evaluations. Evaluation should be based on values of all individuals who may be affected by public or private decisions. There are many evaluation methods for determining how individuals and groups value alternative public actions. Numerous weighting-scaling methodologies can be used in such evaluations. These methodologies represent adaptations of multiple-criteria or multiple-attribute decision-making techniques. Environmental risk assessment which accounts for uncertainties in choosing among alternative policies and projects is increasingly used.

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지구통계 기법을 활용한 토양 오염범위 산정 및 불확실성 평가 (Evaluation of Geostatistical Approaches for better Estimation of Polluted Soil Volume with Uncertainty Evaluation)

  • 김호림;김경호;윤성택;황상일;김형돈;이군택;김영주
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제17권6호
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    • pp.69-81
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    • 2012
  • Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.

CMIP5 MME와 Best 모델의 비교를 통해 살펴본 미래전망: I. 동아시아 기온과 강수의 단기 및 장기 미래전망 (Future Change Using the CMIP5 MME and Best Models: I. Near and Long Term Future Change of Temperature and Precipitation over East Asia)

  • 문혜진;김병희;오효은;이준이;하경자
    • 대기
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    • 제24권3호
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    • pp.403-417
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    • 2014
  • Future changes in seasonal mean temperature and precipitation over East Asia under anthropogenic global warming are investigated by comparing the historical run for 1979~2005 and the Representative Concentration Pathway (RCP) 4.5 run for 2006~2100 with 20 coupled models which participated in the phase five of Coupled Model Inter-comparison Project (CMIP5). Although an increase in future temperature over the East Asian monsoon region has been commonly accepted, the prediction of future precipitation under global warming still has considerable uncertainties with a large inter-model spread. Thus, we select best five models, based on the evaluation of models' performance in present climate for boreal summer and winter seasons, to reduce uncertainties in future projection. Overall, the CMIP5 models better simulate climatological temperature and precipitation over East Asia than the phase 3 of CMIP and the five best models' multi-model ensemble (B5MME) has better performance than all 20 models' multi-model ensemble (MME). Under anthropogenic global warming, significant increases are expected in both temperature and land-ocean thermal contrast over the entire East Asia region during both seasons for near and long term future. The contrast of future precipitation in winter between land and ocean will decrease over East Asia whereas that in summer particularly over the Korean Peninsula, associated with the Changma, will increase. Taking into account model validation and uncertainty estimation, this study has made an effort on providing a more reliable range of future change for temperature and precipitation particularly over the Korean Peninsula than previous studies.

Finite element fracture reliability of stochastic structures

  • Lee, J.C.;Ang, A.H.S.
    • Structural Engineering and Mechanics
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    • 제3권1호
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    • pp.1-10
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    • 1995
  • This study presents a methodology for the system reliability analysis of cracked structures with random material properties, which are modeled as random fields, and crack geometry under random static loads. The finite element method provides the computational framework to obtain the stress intensity solutions, and the first-order reliability method provides the basis for modeling and analysis of uncertainties. The ultimate structural system reliability is effectively evaluated by the stable configuration approach. Numerical examples are given for the case of random fracture toughness and load.

Adaptive Clustering Algorithm for Recycling Cell Formation: An Application of the Modified Fuzzy ART Neural Network

  • Park, Ji-Hyung;Seo, Kwang-Kyu
    • 한국데이타베이스학회:학술대회논문집
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    • 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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    • pp.253-260
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    • 1999
  • The recycling cell formation problem means that disposal products me classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem far disposal products. In this paper, a heuristic approach fuzzy ART neural network is suggested. The modified fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its ai is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

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Quantitative Approaches in Use to Assess Cancer Risk

  • Anderson Elizabeth L.
    • 대한예방의학회:학술대회논문집
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    • 대한예방의학회 1994년도 교수 연수회(환경)
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    • pp.450-468
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    • 1994
  • Scientists have long used conventional toxicological methods to establish 'safe levels of exposure' for chemicals presumed to have threshold health effects or doses below which significant effects are unlikely to occur. These same methods cannot be used to establish safe levels of exposure for non-threshold pollutants. such as carcinogens. Therefore. Federal regulatory agencies in the United States are using risk assessment methods to provide information for public health policy decisions concerning increases in risk associated with increases in exposure to carcinogenic and other non-threshold pollutants. Acceptable exposure/risk levels are decided by policymakers who consider descriptions and estimates of risks together with social and economic benefits from the uses of the chemical. 1bis paper focuses on the development of quantitative risk assessment approaches by Federal regulatory agencies in the United States, and identifies the mathematical models currently being used for risk extrapolation. including their inherent uncertainties. The uncertainties and limitations of these methods have led some scientists to question the utility of quantitative risk extrapolation. The experience of the; U.S. Environmental Protection Agency (EPA). as summarized in this paper. can provide a realistic basis for evaluating the pros and cons. Finally. shortcomings in current risk assessment methods and their use in policy decisions are explored. and areas for possible improvement. given current scientific knowledge. are identified.

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Adaptive Clustering Algorithm for Recycling Cell Formation An Application of the Modified Fuzzy ART Neural Network

  • Park, Ji-Hyung;Seo, Kwang-Kyu
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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    • pp.253-260
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    • 1999
  • The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. In this paper, a heuristic approach for fuzzy ART neural network is suggested. The modified Fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its aim is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

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An Information-based Forecasting Model for Project Progress and Completion Using Bayesian Inference

  • Yoo, Wi-Sung;Hadipriono, Fabian C.
    • 한국건설관리학회논문집
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    • 제8권4호
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    • pp.203-213
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    • 2007
  • In the past, several construction projects have exceeded their schedule resulting in financial losses to the owners; at present there are very few methods available to accurately forecast the completion date of a project. These nay be because of unforeseen outcomes that cannot be accounted for earlier and because of deficiency of proper tools to forecast completion date of said project. To overcome these difficulties, project managers may need a tool to predict the completion date at the early stage of project development. Bayesian Inference introduced in this paper is one such tool that can be employed to forecast project progress at all construction stages. Using this inference, project managers can combine an initially planned project progress (growth curve) with reported information from ongoing projects during the development, and in addition, dynamically revise this initial plan and quantify the uncertainty of completion date. This study introduces a theoretical model and proposes a mathematically information-based framework to forecast a project completion date that corresponds with the actual progress data and to monitor the modified uncertainties using Bayesian Inference.

Seismic risk assessment of intake tower in Korea using updated fragility by Bayesian inference

  • Alam, Jahangir;Kim, Dookie;Choi, Byounghan
    • Structural Engineering and Mechanics
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    • 제69권3호
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    • pp.317-326
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    • 2019
  • This research aims to assess the tight seismic risk curve of the intake tower at Geumgwang reservoir by considering the recorded historical earthquake data in the Korean Peninsula. The seismic fragility, a significant part of risk assessment, is updated by using Bayesian inference to consider the uncertainties and computational efficiency. The reservoir is one of the largest reservoirs in Korea for the supply of agricultural water. The intake tower controls the release of water from the reservoir. The seismic risk assessment of the intake tower plays an important role in the risk management of the reservoir. Site-specific seismic hazard is computed based on the four different seismic source maps of Korea. Probabilistic Seismic Hazard Analysis (PSHA) method is used to estimate the annual exceedance rate of hazard for corresponding Peak Ground Acceleration (PGA). Hazard deaggregation is shown at two customary hazard levels. Multiple dynamic analyses and a nonlinear static pushover analysis are performed for deriving fragility parameters. Thereafter, Bayesian inference with Markov Chain Monte Carlo (MCMC) is used to update the fragility parameters by integrating the results of the analyses. This study proves to reduce the uncertainties associated with fragility and risk curve, and to increase significant statistical and computational efficiency. The range of seismic risk curve of the intake tower is extracted for the reservoir site by considering four different source models and updated fragility function, which can be effectively used for the risk management and mitigation of reservoir.