• Title/Summary/Keyword: joint probability

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Joint Probability Approach to Bias Correction on Rainfall Forecasting Using Climate State Variables (결합확률모델 및 기상변량을 이용한 예측강수의 편의보정 기법)

  • Jung, Min-Kyu;Kim, Tae-Jeong;Hwang, Kyu-Nam;Kwon, Hyun-Han
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.309-309
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    • 2019
  • 기후예측모델을 통해 일단위 강수의 예측정보가 제공되고 있지만, 실제 강수량자료와 시공간적 편의로 인해 수문학적 활용은 한계가 있다. 일반적으로 기후모델의 시공간적 해석 규모 및 예측정확성을 고려할 때 계절단위에서 예측정보의 활용이 가장 현실적인 것으로 알려지고 있다. 그러나 수문해석 시 시공간적 해상도가 낮아 직접적인 활용은 어려운 상황이며, 수문해석 모형의 입력자료로 활용 시 편의보정 및 상세화 과정이 일반적으로 요구된다. 본 연구에서는 기후모델로부터 얻은 강우예측결과에 Bayesian 모델 기반의 편의보정-상세화 기법을 개발하여 강우예측정보의 활용성을 개선하고자 한다. 이 과정에서 Bayesian Copula 모델을 이용한 이변량 형태의 예측강수의 검보정 방법을 개발하였으며, 특히 기후모델 이외의 기상 상태변량인 해수면온도(sea surface temperature, SST)를 예측인자로 추가하여 Hybrid 형태의 계절 앙상블 강우예측모델을 개발하고자 한다.

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A Density Peak Clustering Algorithm Based on Information Bottleneck

  • Yongli Liu;Congcong Zhao;Hao Chao
    • Journal of Information Processing Systems
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    • v.19 no.6
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    • pp.778-790
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    • 2023
  • Although density peak clustering can often easily yield excellent results, there is still room for improvement when dealing with complex, high-dimensional datasets. One of the main limitations of this algorithm is its reliance on geometric distance as the sole similarity measurement. To address this limitation, we draw inspiration from the information bottleneck theory, and propose a novel density peak clustering algorithm that incorporates this theory as a similarity measure. Specifically, our algorithm utilizes the joint probability distribution between data objects and feature information, and employs the loss of mutual information as the measurement standard. This approach not only eliminates the potential for subjective error in selecting similarity method, but also enhances performance on datasets with multiple centers and high dimensionality. To evaluate the effectiveness of our algorithm, we conducted experiments using ten carefully selected datasets and compared the results with three other algorithms. The experimental results demonstrate that our information bottleneck-based density peaks clustering (IBDPC) algorithm consistently achieves high levels of accuracy, highlighting its potential as a valuable tool for data clustering tasks.

Reliability Prediction of Failure Modes due to Pressure in Solid Rocket Case (고체로켓 케이스 내압파열 고장모드의 신뢰도예측)

  • Kim, Dong-Seong;Yoo, Min-Young;Kim, Hee-Seong;Choi, Joo-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.27 no.6
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    • pp.635-642
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    • 2014
  • In this paper, an efficient technique is developed to predict failure probability of three failure modes(case rupture, fracture and bolt breakage) related to solid rocket motor case due to the inner pressure during the mission flight. The overall procedure consists of the steps: 1) design parameters affecting the case failure are identified and their uncertainties are modelled by probability distribution, 2) combustion analysis in the interior of the case is carried out to obtain maximum expected operating pressure(MEOP), 3) stress and other structural performances are evaluated by finite element analysis(FEA), and 4) failure probabilities are calculated for the above mentioned failure modes. Axi-symmetric assumption for FEA is employed for simplification while contact between bolted joint is accounted for. Efficient procedure is developed to evaluate failure probability which consists of finding first an Most Probable Failure Point(MPP) using First-Order Reliability Method(FORM), next making a response surface model around the MPP using Latin Hypercube Sampling(LHS), and finally calculating failure probability by employing Importance Sampling.

Reliability-Based Design Optimization for a Vertical-Type Breakwater with an Emphasis on Sliding, Overturn, and Collapse Failure (직립식 방파제 신뢰성 기반 최적 설계: 활동, 전도, 지반 훼손으로 인한 붕괴 파괴를 중심으로)

  • Yong Jun Cho
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.36 no.2
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    • pp.50-60
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    • 2024
  • To promote the application of reliability-based design within the Korean coastal engineering community, the author conducted reliability analyses and optimized the design of a vertical-type breakwater, considering multiple limit states in the seas off of Pusan and Gunsan - two representative ports in Korea. In this process, rather than relying on design waves of a specific return period, the author intentionally avoided such constraints. Instead, the author characterized the uncertainties associated with wave force, lift force, and overturning moment - key factors significantly influencing the integrity of a vertical-type breakwater. This characterization was achieved by employing a probabilistic model derived from the frequency analysis results of long-term in-situ wave data. The limit state of the vertical-type breakwater encompassed sliding, overturning, and collapse failure, with the close interrelation between wave force, lift force, and moment described using the Nataf joint probability distribution. Simulation results indicate, as expected, that considering only sliding failure underestimates the failure probability. Furthermore, it was shown that the failure probability of vertical-type breakwaters cannot be consistently secured using design waves with a specific return period. In contrast, breakwaters optimally designed to meet the reliability index requirement of 𝛽-3.5 to 4 consistently achieve a consistent failure probability across all sea areas.

Categorical Variable Selection in Naïve Bayes Classification (단순 베이즈 분류에서의 범주형 변수의 선택)

  • Kim, Min-Sun;Choi, Hosik;Park, Changyi
    • The Korean Journal of Applied Statistics
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    • v.28 no.3
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    • pp.407-415
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    • 2015
  • $Na{\ddot{i}}ve$ Bayes Classification is based on input variables that are a conditionally independent given output variable. The $Na{\ddot{i}}ve$ Bayes assumption is unrealistic but simplifies the problem of high dimensional joint probability estimation into a series of univariate probability estimations. Thus $Na{\ddot{i}}ve$ Bayes classier is often adopted in the analysis of massive data sets such as in spam e-mail filtering and recommendation systems. In this paper, we propose a variable selection method based on ${\chi}^2$ statistic on input and output variables. The proposed method retains the simplicity of $Na{\ddot{i}}ve$ Bayes classier in terms of data processing and computation; however, it can select relevant variables. It is expected that our method can be useful in classification problems for ultra-high dimensional or big data such as the classification of diseases based on single nucleotide polymorphisms(SNPs).

An Evaluation of the Emptiness Passage Time of the Kuemgang Estuary Reservoir by Two-Step Transition Model (2단계 추이모형에 의한 금강하구호의 공수도달시간의 평가)

  • Lee, Jae-Hyoung;Chung, Mahn
    • Water for future
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    • v.26 no.3
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    • pp.113-124
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    • 1993
  • This study aims at the evaluation of the stationary distribution and the emptiness passage time for the effectiveness of water utility in the Keumgang estuary reservoir by two-step transition model. It was taken discrete Markovian correlated inflows for the joint probability of inflows and storage, and was used binomial distribution for inflows distribution. As the results, it was decreased from 0.952 to 0.904 the emptiness probability of the reservoir stationary distribution during 1952-1980, and from 0.900 to 0.829 during 1981-1989, and the average emptiness passage time was increased from 23 days to 37 days during 1952-1980, and from 29 days to 61 days during 1981-1989 at low state of storage. From this, it is found that the emptiness passage time is varied with the increase of the inflows auto-correlation coefficient in the Keumgang estuary reservoir. Therefore, it is understood that auto-correlation coefficient must be taken into consideration for the evaluation of water utility in a small reservoir at drought time.

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Study on Predictable Program of Fire.Explosion Accident Using Poisson Distribution Function & Societal Risk Criteria in City Gas (Poisson분포를 이용한 도시가스 화재 폭발사고의 발생 예측프로그램 및 사회적 위험기준에 관한 연구)

  • Ko, Jae-Sun;Kim, Hyo;Lee, Su-Kyoung
    • Fire Science and Engineering
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    • v.20 no.1 s.61
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    • pp.6-14
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    • 2006
  • The data of city gas accidents has been collected and analysed for not only predictions of the fire and explosion accidents but also the criteria of societal risk. The accidents of the recent 11 years have been broken up into such 3 groups roughly as "release", "explosion", "fire" d 16 groups in detail. Owing to the Poisson probability distribution functions, 'careless work-explosion-pipeline' and 'joint loosening & erosion-release-pipeline' items respectively have turned out to record the lowest and most frequency among the recent 11-years accidents. And thus the proper counteractions must be carried out. In order to assess the societal risks tendency of the fatal gas accidents and set the more obvious safety policies up, the D. O. Hogon equation and the regression method has been used to range the acceptable range in the F-N curve of the cumulative casualties. The further works requires setting up successive database on the fire and explosion accidents systematically to obtain reliable analyses. Also the standard codification will be demanded.

Evaluation of Flood Severity Using Bivariate Gumbel Mixed Model (이변량 Gumbel 혼합모형을 이용한 홍수심도 평가)

  • Lee, Jeong-Ho;Chung, Gun-Hui;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.42 no.9
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    • pp.725-736
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    • 2009
  • A flood event can be defined by three characteristics; peak discharge, total flood volume, and flood duration, which are correlated each other. However, a conventional flood frequency analysis for the hydrological plan, design, and operation has focused on evaluating only the amount of peak discharge. The interpretation of this univariate flood frequency analysis has a limitation in describing the complex probability behavior of flood events. This study proposed a bivariate flood frequency analysis using a Gumbel mixed model for the flood evaluation. A time series of annual flood events was extracted from observations of inflow to the Soyang River Dam and the Daechung Dam, respectively. The joint probability distribution and return period were derived from the relationship between the amount of peak discharge and the total volume of flood runoff. The applicability of the Gumbel mixed model was tested by comparing the return periods acquired from the proposed bivariate analysis and the conventional univariate analysis.

Systematic Approach for Predicting Irregular Wave Transformation (불규칙파랑의 계통적 취급수법)

  • 권정곤
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.2 no.2
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    • pp.83-95
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    • 1990
  • It can be assumed that the ocean waves consist of many independent pure sinusoidal components which progress in arbitrary directions. To analyze irregular sea waves, both the spectrum method and the individual wave method have been used. The spectral approach is valid in the region where the water depth is deep and the linear property of velocity distribution is predominent, while the individual wave analysis method in the region where the water depth is shallow and the wave nonlinearity is significant. Therefore, to investigate the irregular wave transformation from the deep water to the shallow water region, it is necessary to relate the frequency spectrum which is estimated by the spectrum analysis method to the i oint probability distribution of wave height, period and direction affected by the boundary condition of the individual wave analysis method. It also becomes important to define the region where both methods can be applied. This study is a part of investigation to establish a systematic approach for analyzing the irregular wave transformation. The region where the spectral approach can be applied is discussed by earring out the experiments on the irregular wave transformation in the two-dimensional wave tank together with the numerical simulation. The applicability of the individual wave analysis method for predicting irregular wave transformation including wave shoaling and breaking and the relation between frequency spectrum and joint probability distribution of wave height and period are also investigated through the laboratory experiment and numerical simualtion.

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Joint Subcarrier and Power Allocation for a Downlink OFDMA Relay Network in Multi-Cell Environments (다중 셀 환경에서 하향 링크 OFDMA 중계 네트워크를 위한 부반송파 및 전력 할당 기법)

  • Choi, Dong-Wook;Lee, Jae-Hong
    • Journal of Broadcast Engineering
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    • v.15 no.2
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    • pp.173-181
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    • 2010
  • In this paper, we propose a new resource allocation scheme for an OFDMA relay network with multicells. In the proposed scheme, by sharing the channel state information (CSI) between base stations, resources are allocated to users and relays to maximize the overall sum of the achievable rate under fairness constraints. In order to reduce the computational complexity, a resource allocation scheme is proposed by separating subcarrier allocation and power allocation into two parts. First of all, by considering inter-cell interference (ICI), a subcarrier is allocated to a user-relay pair, and power is allocated relays. Simulation results show that the proposed scheme achieves higher spectral efficiency per subcarrier than the static scheme and reduces the outage probability compared to the static and greedy schemes.