• 제목/요약/키워드: stochastic simulation.

검색결과 786건 처리시간 0.028초

Bivariate Oscillation Model for Surrogating Climate Change Scenarios in the LCRR basin

  • Lee, Taesam;Ouarda, Taha;Ahn, Yujin
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2021년도 학술발표회
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    • pp.69-69
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    • 2021
  • From the unprecedented 2011 spring flood, the residens reside by Lake Champlain and Richelieu River encountered enormous damages. The International Joint Committee (IJC) released the Lake Champlain-Richelieu River (LCRR) Plan of Study (PoS). One of the major tasks for the PoS is to investigate the possible scenarios that might happen in the LCRR basin based on the stochastic simulation of the Net Basin Supplies that calculates the amount of flow into the lake and the river. Therefore, the current study proposed a novel apporach that simulate the annual NBS teleconnecting the climate index. The proposed model employed the bivariate empirical decomposition to contamporaneously model the long-term evolution of nonstationary oscillation embeded in the annual NBS and the climate signal (here, Artic Oscillation: AO). In order to represent the variational behavior of NBS correlation structure along with the temporal revolution of the climate index, a new nonstationary parameterization concept is proposed. The results indicate that the proposed model is superior performance in preserving long and short temporal correlation. It can even preserve the hurst coefficient better than any other tested models.

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추계론적 방법을 통한 연속 적설 자료 모의 (Simulation of continuous snow accumulation data using stochastic method)

  • 박정하;김동균;이정훈
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.60-60
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    • 2022
  • 본 연구에서는 적설 추정 알고리즘과 추계 일기 생성 모형을 활용하여 관측 적설의 특성을 재현하는 연속 적설심 자료 모의 방법을 소개한다. 적설 추정 알고리즘은 강수 유형 판단, Snow Ratio 추정, 그리고 적설 깊이 감소량 추정까지 총 3단계로 구성된다. 먼저 강수 발생시 지상기온과 상대습도를 지표로 활용하여 강수 유형을 판단하고, 강수가 적설로 판별되었을 때 강수량을 신적설심으로 환산하는 Snow Ratio를 추정한다. Snow Ratio는 지상 기온과의 sigmoid 함수 회귀분석을 통해 추정하였으며, precipitation rate 조건(5 mm/3hr 미만 및 이상)에 따라 두 가지 함수를 적용하였다. 마지막으로 적설 깊이 감소량은 온도 지표 snowmelt 식을 이용하여 추정하였으며, 매개변수는 적설 깊이 및 온도 관측 자료를 활용하여 보정하였다. 속초 관측소 자료를 활용하여 매개변수를 보정 및 검증하여 높은 NSE(보정기간 : 0.8671, 검증기간 : 0.7432)를 달성하였으며, 이 알고리즘을 추계 일기 생성 모형으로 모의한 합성 기상 자료(강수량, 지상기온, 습도)에 적용하여 합성 적설심 시계열을 모의하였다. 모의 자료는 관측 자료의 통계 및 극한값을 매우 정확하게 재현하였으며, 현행 건축구조기준과도 일치하는 것으로 나타났다. 이 모형을 통하여 적설 위험 분석 분야뿐 아니라 기후 전망 자료와의 결합, 미계측 지역에 대한 자료 모의 등에도 광범위하게 활용될 수 있을 것이다.

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Reclaiming Multifaceted Financial Risk Information from Correlated Cash Flows under Uncertainty

  • Byung-Cheol Kim;Euysup Shim;Seong Jin Kim
    • 국제학술발표논문집
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    • The 5th International Conference on Construction Engineering and Project Management
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    • pp.602-607
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    • 2013
  • Financial risks associated with capital investments are often measured with different feasibility indicators such as the net present value (NPV), the internal rate of return (IRR), the payback period (PBP), and the benefit-cost ratio (BCR). This paper aims at demonstrating practical applications of probabilistic feasibility analysis techniques for an integrated feasibility evaluation of the IRR and PBP. The IRR and PBP are concurrently analyzed in order to measure the profitability and liquidity, respectively, of a cash flow. The cash flow data of a real wind turbine project is used in the study. The presented approach consists of two phases. First, two newly reported analysis techniques are used to carry out a series of what-if analyses for the IRR and PBP. Second, the relationship between the IRR and PBP is identified using Monte Carlo simulation. The results demonstrate that the integrated feasibility evaluation of stochastic cash flows becomes a more viable option with the aide of newly developed probabilistic analysis techniques. It is also shown that the relationship between the IRR and PBP for the wind turbine project can be used as a predictive model for the actual IRR at the end of the service life based on the actual PBP of the project early in the service life.

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동적 신뢰성 해석 기법의 수치 안정성에 관하여 (On the Numerical Stability of Dynamic Reliability Analysis Method)

  • 이도근;옥승용
    • 한국안전학회지
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    • 제35권3호
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    • pp.49-57
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    • 2020
  • In comparison with the existing static reliability analysis methods, the dynamic reliability analysis(DyRA) method is more suitable for estimating the failure probability of a structure subjected to earthquake excitations because it can take into account the frequency characteristics and damping capacity of the structure. However, the DyRA is known to have an issue of numerical stability due to the uncertainty in random sampling of the earthquake excitations. In order to solve this numerical stability issue in the DyRA approach, this study proposed two earthquake-scale factors. The first factor is defined as the ratio of the first earthquake excitation over the maximum value of the remaining excitations, and the second factor is defined as the condition number of the matrix consisting of the earthquake excitations. Then, we have performed parametric studies of two factors on numerical stability of the DyRA method. In illustrative example, it was clearly confirmed that the two factors can be used to verify the numerical stability of the proposed DyRA method. However, there exists a difference between the two factors. The first factor showed some overlapping region between the stable results and the unstable results so that it requires some additional reliability analysis to guarantee the stability of the DyRA method. On the contrary, the second factor clearly distinguished the stable and unstable results of the DyRA method without any overlapping region. Therefore, the second factor can be said to be better than the first factor as the criterion to determine whether or not the proposed DyRA method guarantees its numerical stability. In addition, the accuracy of the numerical analysis results of the proposed DyRA has been verified in comparison with those of the existing first-order reliability method(FORM), Monte Carlo simulation(MCS) method and subset simulation method(SSM). The comparative results confirmed that the proposed DyRA method can provide accurate and reliable estimation of the structural failure probability while maintaining the superior numerical efficiency over the existing methods.

계층적 베이지안 ARX 모형을 활용한 염분모의기법 개발 (Development of salinity simulation using a hierarchical bayesian ARX model)

  • 김호준;신충훈;김태웅;권현한
    • 한국수자원학회논문집
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    • 제53권7호
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    • pp.481-491
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    • 2020
  • 새만금 농업단지가 조성됨에 따라 농업용수 공급이 요구되며, 농업적 측면에서 염분은 작물 재배시 생육에 영향을 미치는 항목으로 농업용수 공급시 철저한 관리가 요구된다. 따라서 농작물에 영향을 미치지 않는 농업용수 공급을 위해 염분계측을 통한 체계적인 농업용수 관리가 필요하다. 본 연구에서는 새만금호내에 관측되는 염분 시계열 자료를 모의하기 위해서 자기회귀모형을 기반으로 한 Two-Stage ARX 모형을 개발하였다. 층별로 나눠진 염분자료를 계층적 Bayesian기법을 활용하여 매개변수를 확률분포형으로 추정하였으며 염분모의의 불확실성을 제시하였다. 최적 모형을 선정하기 위해서 통계적 지표인 BIC값을 이용하였으며, 최종적으로 선정된 모형을 통해 양수장 인근 수역의 염분 모의 결과를 제시하였다.

노이즈 환경에서 입자 군집 최적화 알고리즘의 성능 향상을 위한 통계적 가설 검정 기반 리샘플링 기법의 적용 (Application of Resampling Method based on Statistical Hypothesis Test for Improving the Performance of Particle Swarm Optimization in a Noisy Environment)

  • 최선한
    • 한국시뮬레이션학회논문지
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    • 제28권4호
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    • pp.21-32
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    • 2019
  • 군집에 대한 사회적 행동 모델에 영감을 받은 군집 최적화 알고리즘은 복잡한 최적화 문제 해결에서부터 인공 신경망의 학습에까지 활용되는 대표적인 메타휴리스틱 최적화 알고리즘 중의 하나이다. 하지만 이 알고리즘은 기본적으로 확률적 노이즈가 존재하지 않는 결정적인 환경에서 개발되었기 때문에, 많은 경우 확률적 노이즈가 존재하는 실제 문제에 적용하기에 어려움이 있었다. 본 논문에서는 이를 개선하기 위하여 불확실 평가 기법이라고 정의되는 통계적 가설 검정 기반의 리샘플링 기법을 적용한다. 이 기법을 통하여 입자 군집 최적화 알고리즘의 성능에 가장 큰 영향을 미치는 입자들의 전역 최적을 정확하게 찾으므로 노이즈 환경에서 입자들이 최적해로 보다 정확하고 빠르게 수렴하도록 한다. 다양한 벤치마크 문제들에 대한 기존 알고리즘들과의 비교 실험 결과는 제안하는 알고리즘의 개선된 성능을 입증하고, 사례 연구의 결과는 본 연구의 필요성을 강조한다. 본 연구 결과가 4차 산업혁명 시대에 디지털 트윈 등을 통한 시뮬레이션 기반 시스템 최적화에 효과적으로 적용될 수 있을 것이라 기대한다.

Using Mobile Data Collectors to Enhance Energy Efficiency a nd Reliability in Delay Tolerant Wireless Sensor Networks

  • Yasmine-Derdour, Yasmine-Derdour;Bouabdellah-Kechar, Bouabdellah-Kechar;Faycal-Khelfi, Mohammed
    • Journal of Information Processing Systems
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    • 제12권2호
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    • pp.275-294
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    • 2016
  • A primary task in wireless sensor networks (WSNs) is data collection. The main objective of this task is to collect sensor readings from sensor fields at predetermined sinks using routing protocols without conducting network processing at intermediate nodes, which have been proved as being inefficient in many research studies using a static sink. The major drawback is that sensor nodes near a data sink are prone to dissipate more energy power than those far away due to their role as relay nodes. Recently, novel WSN architectures based on mobile sinks and mobile relay nodes, which are able to move inside the region of a deployed WSN, which has been developed in most research works related to mobile WSN mainly exploit mobility to reduce and balance energy consumption to enhance communication reliability among sensor nodes. Our main purpose in this paper is to propose a solution to the problem of deploying mobile data collectors for alleviating the high traffic load and resulting bottleneck in a sink's vicinity, which are caused by static approaches. For this reason, several WSNs based on mobile elements have been proposed. We studied two key issues in WSN mobility: the impact of the mobile element (sink or relay nodes) and the impact of the mobility model on WSN based on its performance expressed in terms of energy efficiency and reliability. We conducted an extensive set of simulation experiments. The results obtained reveal that the collection approach based on relay nodes and the mobility model based on stochastic perform better.

활 전복 수입에 의한 전복허피스바이러스감염증 (abalone herpes-like virus) 유입 위험평가 (A Stochastic Model to Quantify the Risk of Introduction of Abalone Herpes-like Virus Through Import of Abalones)

  • 박선일
    • 한국임상수의학회지
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    • 제31권1호
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    • pp.40-45
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    • 2014
  • Abalone herpes-like virus (AbHV) is a fatal disease of abalones that impose severe economic impacts on the industry of infected regions due to high mortality. The aim of this study was to quantify the risk of introducing AbHV into Korea through the importation of live abalones for human consumption by import risk analysis (IRA). Monte Carlo simulation models were developed to provide estimates of the probability that a ton of imported abalone contains at least one AbHV-infected individual, using historical trade data and relevant literatures. A sensitivity analysis with 5,000 iterations was also conducted to determine the extent to which input parameters affect the outcome of the model. Although many uncertainties were present in the data, the results indicated that, if 5,000 tons of abalone were imported from a hypothetical exporting country with low prevalence of AbHV (model 1), there would be at least one AbHV-infected abalones in 4,816 of those tons (96.3%), while there would be at least one AbHV-infected abalones in 100% of those tons imported from country with high prevalence (model 2). Sensitivity analysis indicated that for model 1, prevalence was the strongest influence factor on the predicted number of infections. For model 2, background mortality and washing to reduce the risk of surface contamination during processing were the major contributing factors. Risk management strategies need to be enforced to reduce the risk of AbHV introduction in that at least one infected abalone would remain in a consignment from country even with a low prevalence of AbHV infection. The methodology and the results presented here will contribute to improve the development of AbHV management program, and with more accurate data this IRA model will aid science-based decision-making on mitigation strategies to reduce the risk of AbHV introduction in Korea.

Layout optimization of wireless sensor networks for structural health monitoring

  • Jalsan, Khash-Erdene;Soman, Rohan N.;Flouri, Kallirroi;Kyriakides, Marios A.;Feltrin, Glauco;Onoufriou, Toula
    • Smart Structures and Systems
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    • 제14권1호
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    • pp.39-54
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    • 2014
  • Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

실시간 범람위험도 예측을 위한 수리학적 모형의 개발 (Hydraulic Model for Real Time Forecasting of Inundation Risk)

  • 한건연;손인호;이재영
    • 한국수자원학회논문집
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    • 제33권3호
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    • pp.331-340
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    • 2000
  • 본 연구의 목적은 하천에서의 실시간 범람위험도 해석을 위해서 DAMBRK 모형과 Kalman filter를 연계한 수치모형을 개발하는데 있다. 본 모형은 1차원 동역학 방정식의 비선형 유한차분 근사해인 음해법을 기본으로 하고 있다. 추계학적 추정법으로서 최적의 갱신 예측치를 얻기 위해 확장된 Kalman filter 기법을 사용하였다. 이 과정은 확정론적 모형에 의한 예측치를 Kalman filter gain factor에 의해 보정된 실시간 관측치와 조합함으로써 수행되었다. 홍수범람위험도는 하도단면의 기하형상과 Manning 조도계수의 변동성을 고려하여 Monte Carlo 모의를 적용하여 예측되었다. 본 모형은 1990년 9월과 1995년 8월의 남한강 홍수에 적용하여 검증하였다. Kalman filter에 의한 해석은 이 기간 동안에 확정론적 해석결과와 비교하여 실측자료와 잘 일치되는 양상이 나타났으며, 이에 따라 제방의 월류위험도를 모의된 홍수위와 제방고를 비교함으로써 얻을 수 있었다.

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