• Title/Summary/Keyword: 추계적 모형

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Prediction of cyanobacteria population based on Poisson regression based on hydro-meteorological condition (수문기상 조건을 고려한 Poisson regression 기반의 Cyanobacteria 개체수 예측)

  • Cho, Hemie;Huong, Nguyen Thi;Moon, Jangwon;Kwon, Hyun-Han
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.208-208
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    • 2020
  • 지구온난화와 하천환경의 변화로 수질 오염이 심각해지고 녹조 현상 등의 피해가 증가하고 있다. 특히, 기후변화로 인해 온도와 강우량의 변동성이 동시에 증가하고 있어 하천의 수환경 관리측면에서 어려움이 증가하고 있다. 최근 하천 개발 사업으로 인한 인공 구조물 축조로 하천의 오염도 변화는 중요한 논점으로 대두되었으며, 그에 따라 정확한 수질 전망이 요구되고 있다. 녹조평가에 있어 주요 대리변수(proxy variable)로 chlorophyll-a(Chl-a)가 사용되고 있지만, Chl-a는 규조류와 남조류(cyanobacteria) 모두에서 발견되는 지표로서, 녹조의 유해성을 Chl-a 수질 지표만을 사용하여 판단하기에는 한계가 있다. Chl-a뿐만 아니라 수질에 대한 유량, 온도, 영양염류 등의 영향 또한 기존 연구에서 밝혀진 바 있다. 하지만 기존의 물리기반의 결정론적모형은 수질의 추계학적(stochastic) 특성을 반영하는데 제한적이며, 다양한 수문기상학적 조건을 고려한 시나리오 기반의 분석을 수행하는데 한계가 있다. 따라서 본 연구에서는 특정 지점의 보 건설 이후 수문기상 자료를 이용하여 유해 남조류 개체수와 관계있는 수문기상학적 요인을 평가하고 최종적으로 Bayesian Poisson Regression 기반의 중·장기 녹조 예측 모형을 개발하였으며, 해설결과에 대한 불확실성 정보도 제공할 수 있도록 하였다.

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GCM Scenario Downcsaling Method using Multi-Artificial Neural Network and Stochastic Typhoon Model (다지점 인공신경망과 추계학적 태풍모의를 통한 GCM 시나리오 상세화기법)

  • Moon, Su-Jin;Kim, Jung-Joong;Kang, Boo-Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.276-276
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    • 2012
  • 일반적으로 기후변화영향에 관한 연구수행을 위해 전지구기후모형(GCM; Global Climate Model)이 사용되고 있다. 하지만 GCM은 공간해상도(Spatial resolution)가 거칠기 때문에 수문학 분야에서 주로 사용되는 유역규모의 지역적인 스케일특성과 물리적 특징을 표현하는데 한계가 있다. 또한 GCM 기후변수들 중 강수량의 경우 한반도 지역의 6월과 10월 사이에 연강수량의 67% 이상이 집중되는 계절성을 반영하지 못하고 있으며, 높은 불확실성을 보이고 있다. 본 연구에서는 GCM 기반의 다지점 인공신경망기법을 적용한 상세화(Downscaling)를 실시하였다. GCM의 24개 2D변수에 대한 주성분분석을 실시하여 신경망의 학습인자로 사용하였으며, 학습, 검증 및 예측기간은 각각 1981~1995년, 1996~2000년, 2011~2100년으로 A1B 시나리오를 대상으로 상세화를 실시하였다. 또한, 여름철 태풍사상을 모의하기 위한 Stochastic Typhoon Simulation기법과 Baseline과 Projection 사이의 강수량 보정을 위한 Dynamic Quantile Mapping 기법을 적용하여, 강수량의 불확실성을 최소화 하고자 하였다.

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A simple approach to simulate the size distribution of suspended sediment (부유사 입경분포 모의를 위한 간편법)

  • Kwon, Minhyuck;Byun, Jisun;Son, Minwoo
    • Journal of Korea Water Resources Association
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    • v.57 no.5
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    • pp.347-357
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    • 2024
  • Numerous prior studies have delineated the size distribution of noncohesive sediment in suspension, focusing on mean size and standard deviation. However, suspensions comprise a heterogeneous mixture of sediment particles of varying sizes. The transport dynamics of suspended sediment in turbulent flow are intimately tied to settling velocities calculated based on size and density. Consequently, understanding the grain size distribution becomes paramount in comprehending sediment transport phenomena for noncohesive sediment. This study aims to introduce a straightforward modeling approach for simulating the grain size distribution of suspended sediment amidst turbulence. Leveraging insights into the contrast between cohesive and noncohesive sediment, we have meticulously revised a stochastic flocculation model originally designed for cohesive sediment to aptly simulate the grain size distribution of noncohesive sediment in suspension. The efficacy of our approach is corroborated through a meticulous comparison between experimental data and the grain size distribution simulated by our newly proposed model. Through numerical simulations, we unveil that the modulation of grain size distribution of suspended sediment is contingent upon the sediment transport capacity of the carrier fluid. Hence, we deduce that our simplified approach to simulating the grain size distribution of suspended sediment, integrated with a sediment transport model, serves as a robust framework for elucidating the pivotal bulk properties of sediment transport.

Can 'Buy-One Give-One' Business Model be Profitable? ('Buy-One Give-One' 비즈니스모델의 수익 구조에 대한 수리적 분석)

  • Han, Yunsun;Seo, Youngdoc
    • Review of Culture and Economy
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    • v.20 no.1
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    • pp.3-20
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    • 2017
  • This study proposes that the cultural corporation can be more profitable by adopting the 'Buy-One Give-One' Business Model (BOGO BM) under certain conditions. Specifically, the conditions are that 1) consumers' utility for donating is high enough and 2) the production cost is low enough due to economies of scale or process innovation from employee's intrinsic motivation. We adopt a mathematical model where the demand function is a simple linear function and two companies compete with each other by choosing their quantity of output (the Cournot model). Specifically, we investigate the profitability of the BOGO BM in four situations: 1) a monopolist enjoying reduced cost due to process innovation from employee's intrinsic motivation, 2) a monopolist enjoying reduced cost due to economies of scale, 3) the duopoly with BOGO BM and a general company, 4) the duopoly with two BOGO BM companies. In each situation, BOGO BM can be more profitable than other general companies can under certain conditions.

Cumulative damage calculation model for water distribution system with increasing service year (사용연수 증가에 따른 상수관망의 누적피해도 산정 모형)

  • Kim, Hyeong Gi;Kwon, Hyuk Jae
    • Journal of Korea Water Resources Association
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    • v.57 no.8
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    • pp.561-569
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    • 2024
  • In this study, a damage estimation model for water distribution system was developed to quantitatively calculate the cumulative damage of water distribution system. And it was applied to real water distribution system to analyze the cumulative damage of water distribution system. To analyze the overall damage rate of the water distribution system, the cumulative damage analysis formula of individual pipes was established. And the aging index that affects the damage rate was analyzed using MCS (Monte Carlo Simulation), and Romanoff's measured data was used to calculate the thickness change due to corrosion. In addition, a cumulative damage estimation model was applied to unit network such as small and medium block network, and the cumulative damage of the unit network for up to 50 years was calculated. From the results, it was found that the cumulative damage rate is increased from 7% to 79% for the water distribution system of Naeduk 1-dong, Cheongju City, as the age of the pipeline is increased from 20 years to 50 years.

Efficient Structral Safety Monitoring of Large Structures Using Substructural Identification (부분구조추정법을 이용한 대형구조물의 효율적인 구조안전도 모니터링)

  • 윤정방;이형진
    • Journal of the Earthquake Engineering Society of Korea
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    • v.1 no.2
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    • pp.1-15
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    • 1997
  • This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.

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Study on Water Stage Prediction Using Hybrid Model of Artificial Neural Network and Genetic Algorithm (인공신경망과 유전자알고리즘의 결합모형을 이용한 수위예측에 관한 연구)

  • Yeo, Woon-Ki;Seo, Young-Min;Lee, Seung-Yoon;Jee, Hong-Kee
    • Journal of Korea Water Resources Association
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    • v.43 no.8
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    • pp.721-731
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    • 2010
  • The rainfall-runoff relationship is very difficult to predict because it is complicate factor affected by many temporal and spatial parameters of the basin. In recent, models which is based on artificial intelligent such as neural network, genetic algorithm fuzzy etc., are frequently used to predict discharge while stochastic or deterministic or empirical models are used in the past. However, the discharge data which are generally used for prediction as training and validation set are often estimated from rating curve which has potential error in its estimation that makes a problem in reliability. Therefore, in this study, water stage is predicted from antecedent rainfall and water stage data for short term using three models of neural network which trained by error back propagation algorithm and optimized by genetic algorithm and training error back propagation after it is optimized by genetic algorithm respectively. As the result, the model optimized by Genetic Algorithm gives the best forecasting ability which is not much decreased as the forecasting time increase. Moreover, the models using stage data only as the input data give better results than the models using precipitation data with stage data.

Future Inflow Simulation Considering the Uncertainties of TFN Model and GCMs on Chungju Dam Basin (TFN 모형과 GCM의 불확실성을 고려한 충주댐 유역의 미래 유입량 모의)

  • Park, Jiyeon;Kwon, Ji-Hye;Kim, Taereem;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.47 no.2
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    • pp.135-143
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    • 2014
  • In this study, Chungju inflow was simulated for climate change considering the uncertainties of GCMs and a stochastic model. TFN (Transfer Function Noise) model and 4 different GCMs (CNRM, CSIRO, CONS, UKMO) based on IPCC AR4 A2 scenario were used. In order to evaluate uncertainty of TFN model, 100 cases of noises are applied to the TFN model. Thus, 400 cases of inflow results are simulated. Future inflows according to the GCMs show different rates of changes for the future 3 periods relative to the past 30-years reference period. As the results, the summer inflow shows increasing trend and the spring inflow shows decreasing trend based on AR4 A2 scenario.

A Study on the Alternative to Estimate the Design Low-Flow based on the Runoff Hydrology and the Dry Spell Stochastics (수문-추계 결합법에 의한 설계갈수량 추정법 연구)

  • Lee, Jae-Hyoung;Yoon, Jae-Min
    • Journal of Korea Water Resources Association
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    • v.35 no.4 s.129
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    • pp.375-384
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    • 2002
  • This study is to suggest a method to estimate the design low-flow based on the runoff hydrology. The recession time model to transform a return period into the recession time is derived under the similarity between dry spell and low-flow runoffs event. The proposed recession model can be applied to the gaging station and the ungaged outlet. This recession time model contains the parameters: for climate conditions, watershed characteristics, and runoff characteristics etc. And the recession model is composed of the parameters which are initial discharge and recession constant. This model is applied to the Yongdam gaging station and the other temporary gaging station. Consequently, it is proved that this model can be used for an alternative practice to estimate the design low-flow at the gaging station with short-term runoff data or the ungaged outlet.

Risk Assessment of Levee Embankment Applying Reliability Index (신뢰도 지수를 적용한 하천제방의 위험도 평가)

  • Ahn, Ki-Hong;Han, Kun-Yeun;Kim, Byung-Hyun
    • Journal of Korea Water Resources Association
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    • v.42 no.7
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    • pp.547-558
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    • 2009
  • General reliability assessment of levees embankment is performed with safety factors for rainfall characteristics and hydrologic and hydraulic parameters, based on the results of deterministic analysis. The safety factors are widely employed in the field of engineering handling model parameters and the diversity of material properties, but cannot explain every natural phenomenon. Uncertainty of flood analysis and related parameters by introducing stochastic method rather than deterministic scheme will be required to deal with extreme weather and unprecedented flood due to recent climate change. As a consequence, stochastic-method-based measures considering parameter uncertainty and related factors are being established. In this study, a variety of dimensionless cumulative rainfall curve for typhoon and monsoon season of July to September with generation method of stochastic temporal variation is generated by introducing Monte Carlo method and applied to the risk assessment of levee embankment using reliability index. The result of this study reflecting temporal and regional characteristics of a rainfall can be used for the establishment of flood defence measures, hydraulic structure design and analysis on a watershed.