• Title/Summary/Keyword: 결합분포확률

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Location Benefit Analysis According to Flood Safety Increase (치수안전도 향상에 따른 자산이용고도화 효과 분석)

  • Lee, Jin Ouk;Choi, Seung An;Kim, Hung Soo;Shim, Myung Phil
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.777-783
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    • 2004
  • 하천 세내지 주변은 급속한 시가지 조성과 인구밀집으로 유역의 불투수층이 증가하여 홍수도달시간이 짧아지고 홍수유출량이 증가하고 있다. 또한 엘리뇨${\cdot}$라니냐 등의 이상기후로 홍수사상의 발생 빈도와 규모가 증가하면서 홍수피해도 대형화되어 가고 있다. 그러나 치수사업은 다른 공공사업에 비해 경제성이 저평가 되어 투자우선순위가 밀려 사업시행이 지연되고 예방적 차원의 대책도 미흡하여 피해가 증가하는 악순환이 계속되고 있다. 따라서 본 인구에서는 우리나라의 치수경제성 분석에 있어 계량화하지 못하고 있는 자산이용고도화 효과를 치수안전도와 더불어 분석하고자 한다. 자산이용고도화는 치수사업 시행으로 해당지역의 치수안전도 향상에 따른 자산가치의 상승을 말하는데, 특정지역의 자산가치를 가장 객관적으로 표현할 수 있는 공시지가를 근거로 분석을 수행하였다. 치수사업 시행으로 인한 편익과 하천 특성에 따른 지가변동률의 차이가 통계적으로 유의성이 있는지를 분산분석을 통해 검증하였으면, 자산가치의 상승을 순수 연평균지가변동률로 나타내었다. 치수안전도는 홍수피해 잠재성과 홍수방어능력으로 구분하였는데 홍수피해 잠재성은 도시화율에 따라 구분하였고, 홍수방어능력은 홍수량의 빈도해석과 불확실성을 고려하여 조건부 비초과확률로 나타내었다. 본 연구에서는 소도시 지역(경안천, 복하천, 청미천)을 대상으로 200년 빈도의 홍수사상에 내해 10년, 50년 설계빈도로 건설된 제방의 조건부 비초과확률을 산정하여 지가변동률의 추이를 비교 분석하였다. 분석 결과, 소도시 지역에서는 조건부 비초과확률이 $10\%$ 상승했을 때 순수 연평균지가변동률이 5배정도 상승함을 알 수 있었다.다시 입력자료로 사용하는 업데이트 방식을 사용하기 때문에 예측결과의 오차가 완전하게 보정되지 않으면 다음 결과에 역시 오차를 주게 되어 오차보정이 상당히 중요하다는 것을 알 수 있었다. 오차를 보다 효과적으로 보정하기 위해서는 퍼지제어에 사용되는 퍼지규칙의 수를 늘리고, 유입량에 직접적인 영향을 주는 강우량과 연계한 2변수의 Fuzzy-Grey 모형을 이용한다면 보다 정확한 유입량 예측이 가능할 것으로 사료된다.이 작은 오차를 발생하였으며, 전체적으로 퍼프 모형이 입자모형보다는 훨씬 적은 수의 계산을 통해서도 작은 오차를 나타낼 수 있다는 것을 알 수 있었다. 그러나 Gaussian 분포를 갖는 퍼프모형은 전단흐름에서의 긴 유선형 농도분포를 모의할 수 없었고, 이에 관한 오차는 전단계수가 증가함에 따라 비선형적으로 증가하였다. 향후, 보다 다양한 흐름영역에서 장${\cdot}$단점 분석 및 오차해석을 수행한 후에 각각의 Lagrangian 모형의 장점만을 갖는 모형결합 방법을 제시할 수 있을 것으로 판단된다.mm/$m^{2}$로 감소한 소견을 보였다. 승모판 성형술은 전 승모판엽 탈출증이 있는 두 환아에서 동시에 시행하였다. 수술 후 1년 내 시행한 심초음파에서 모든 환아에서 단지 경등도 이하의 승모판 폐쇄 부전 소견을 보였다. 수술 후 조기 사망은 없었으며, 합병증으로는 유미흉이 한 명에서 있었다. 술 후 10개월째 허혈성 확장성 심근증이 호전되지 않아 Dor 술식을 시행한 후 사망한 예를 제외한 나머지 6명은 특이 증상 없이 정상 생활 중이다 결론: 좌관상동맥 페동맥이상 기시증은 드물기는 하나, 영유아기에 심근경색 및 허혈성 심근증 또는 선천성 승모

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A Methodology of Estimating Design Waves for the Operable Harbor Condition Using Long-term Wave Data (장기 파랑측정자료를 이용한 평상파 산정 방법론)

  • Ahn Kyungmo;Chun Je Ho
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.16 no.3
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    • pp.178-189
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    • 2004
  • For designing a reliable harbor, a methodology for estimating design waves of 97.5% operable harbor condition is suggested using long-term wave data. For a practical application of the methodology, a marine police harbor was selected as a site. Wave data used were collected from February 1993 to December 2003 at Jodo wave gage station in front of Pusan harbor. Joint distributions of significant wave height and significant wave period for specified wave directions were obtained and used to feed as input waves for parabolic mild-slope wave model. Results showed that input waves with significant wave height of 1.75 m, significant wave period off sec and wave direction E yield design waves height of 1.06 m at the site of interests, which is a 97.5% operable harbor condition. Wind waves generated inside harbor showed to be no effect on the design wave condition. Swells propagated from deep water into harbor are shown to be dominant effects on the design waves of operable harbor condition.

A Quantitative Trust Model with consideration of Subjective Preference (주관적 선호도를 고려한 정량적 신뢰모델)

  • Kim, Hak-Joon;Lee, Sun-A;Lee, Kyung-Mi;Lee, Keon-Myung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.1
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    • pp.61-65
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    • 2006
  • This paper is concerned with a quantitative computational trust model which lakes into account multiple evaluation criteria and uses the recommendation from others in order to get the trust value for entities. In the proposed trust model, the trust for an entity is defined as the expectation for the entity to yield satisfactory outcomes in the given situation. Once an interaction has been made with an entity, it is assumed that outcomes are observed with respect to evaluation criteria. When the trust information is needed, the satisfaction degree, which is the probability to generate satisfactory outcomes for each evaluation criterion, is computed based on the outcome probability distributions and the entity's preference degrees on the outcomes. Then, the satisfaction degrees for evaluation criteria are aggregated into a trust value. At that time, the reputation information is also incorporated into the trust value. This paper presents in detail how the trust model works.

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.

Development of a Vehicle Positioning Algorithm Using Reference Images (기준영상을 이용한 차량 측위 알고리즘 개발)

  • Kim, Hojun;Lee, Impyeong
    • Korean Journal of Remote Sensing
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    • v.34 no.6_1
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    • pp.1131-1142
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    • 2018
  • The autonomous vehicles are being developed and operated widely because of the advantages of reducing the traffic accident and saving time and cost for driving. The vehicle localization is an essential component for autonomous vehicle operation. In this paper, localization algorithm based on sensor fusion is developed for cost-effective localization using in-vehicle sensors, GNSS, an image sensor and reference images that made in advance. Information of the reference images can overcome the limitation of the low positioning accuracy that occurs when only the sensor information is used. And it also can acquire estimated result of stable position even if the car is located in the satellite signal blockage area. The particle filter is used for sensor fusion that can reflect various probability density distributions of individual sensors. For evaluating the performance of the algorithm, a data acquisition system was built and the driving data and the reference image data were acquired. Finally, we can verify that the vehicle positioning can be performed with an accuracy of about 0.7 m when the route image and the reference image information are integrated with the route path having a relatively large error by the satellite sensor.

Derived I-D-F Curve in Seoul Using Bivariate Precipitation Frequency Analysis (이변량 강우 빈도해석을 이용한 서울지역 I-D-F 곡선 유도)

  • Kwon, Young-Moon;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2B
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    • pp.155-162
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    • 2009
  • Univariate frequency analyses are widely used in practical hydrologic design. However, a storm event is usually characterized by amount, intensity, and duration of the storm. To fully understand these characteristics and to use them appropriately in hydrologic design, a multivariate statistical approach is necessary. This study applied a Gumbel mixed model to a bivariate storm frequency analysis using hourly rainfall data collected for 46 years at the Seoul rainfall gauge station in Korea. This study estimated bivariate return periods of a storm such as joint return periods and conditional return periods based on the estimation of joint cumulative distribution functions of storm characteristics. These information on statistical behaviors of a storm can be of great usefulness in the analysis and assessment of the risk associated with hydrologic design problems.

Evaluation of Drought Risk in Gyeongsang-do Using EDI (EDI를 활용한 경상도 지역의 가뭄위험도 평가)

  • Park, Jong Yong;Yoo, Ji Young;Choi, Minha;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.3B
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    • pp.243-252
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    • 2011
  • The change of rainfall pattern due to recent climate change increases the occurrence probability of drought in Korea. Unlike other natural disasters, a drought has long duration, extensive area subject to damage, and greater socioeconomic damage than other disasters. In order to evaluate drought severity, meteorological drought indices are mainly used in practice. This study presents a more realistic method to evaluate drought severity considering drought climate factors as well as socioeconomic factors which are vulnerable to disaster. To perform a spatial evaluation of drought risk in Gyeongsang-do, drought risk was defined and analyzed through the hazard index and the vulnerability index. The drought hazard index was spatially assessed using the drought index and GIS. The drought vulnerability index was also spatially assessed using the 5 socioeconomic factors. As a result, the drought risks were compared and used for evaluating regional drought risk considering regional characteristics of Gyeongsang-do.

An Efficient Knowledge Base Management Using Hybrid SOM (하이브리드 SOM을 이용한 효율적인 지식 베이스 관리)

  • Yoon, Kyung-Bae;Choi, Jun-Hyeog;Wang, Chang-Jong
    • The KIPS Transactions:PartB
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    • v.9B no.5
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    • pp.635-642
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    • 2002
  • There is a rapidly growing demand for the intellectualization of information technology. Especially, in the area of KDD (Knowledge Discovery in Database) which should make an optimal decision of finding knowledge from a large amount of data, the demand is enormous. A large volume of Knowledge Base should be efficiently managed for a more intellectual choice. This study is proposing a Hybrid SOM for an efficient search and renewal of knowledge base, which combines a self-study nerve network, Self-Organization Map with a probable distribution theory in order to get knowledge needed for decision-making management from the Knowledge Base. The efficient knowledge base management through this proposed method is carried out by a stimulation test. This test confirmed that the proposed Hybrid SOM can manage with efficiency Knowledge Base.

Application of Spatial Data Integration Based on the Likelihood Ratio Function nad Bayesian Rule for Landslide Hazard Mapping (우도비 함수와 베이지안 결합을 이용한 공간통합의 산사태 취약성 분석에의 적용)

  • Chi, Kwang-Hoon;Chung, Chang-Jo F.;Kwon, Byung-Doo;Park, No-Wook
    • Journal of the Korean earth science society
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    • v.24 no.5
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    • pp.428-439
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    • 2003
  • Landslides, as a geological hazard, have caused extensive damage to property and sometimes result in loss of life. Thus, it is necessary to assess vulnerable areas for future possible landslides in order to mitigate the damage they cause. For this purpose, spatial data integration has been developed and applied to landslide hazard mapping. Among various models, this paper investigates and discusses the effectiveness of the Bayesian spatial data integration approach to landslide hazard mapping. In this study, several data sets related to landslide occurrences in Jangheung, Korea were constructed using GIS and then digitally represented using the likelihood ratio function. By computing the likelihood ratio, we obtained quantitative relationships between input data and landslide occurrences. The likelihood ratio functions were combined using the Bayesian combination rule. In order for predicted results to provide meaningful interpretations with respect to future landslides, we carried out validation based on the spatial partitioning of the landslide distribution. As a result, the Bayesian approach based on a likelihood ratio function can effectively integrate various spatial data for landslide hazard mapping, and it is expected that some suggestions in this study will be helpful to further applications including integration and interpretation stages in order to obtain a decision-support layer.

Performance Improvement of Speaker Recognition by MCE-based Score Combination of Multiple Feature Parameters (MCE기반의 다중 특징 파라미터 스코어의 결합을 통한 화자인식 성능 향상)

  • Kang, Ji Hoon;Kim, Bo Ram;Kim, Kyu Young;Lee, Sang Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.6
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    • pp.679-686
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    • 2020
  • In this thesis, an enhanced method for the feature extraction of vocal source signals and score combination using an MCE-Based weight estimation of the score of multiple feature vectors are proposed for the performance improvement of speaker recognition systems. The proposed feature vector is composed of perceptual linear predictive cepstral coefficients, skewness, and kurtosis extracted with lowpass filtered glottal flow signals to eliminate the flat spectrum region, which is a meaningless information section. The proposed feature was used to improve the conventional speaker recognition system utilizing the mel-frequency cepstral coefficients and the perceptual linear predictive cepstral coefficients extracted with the speech signals and Gaussian mixture models. In addition, to increase the reliability of the estimated scores, instead of estimating the weight using the probability distribution of the convectional score, the scores evaluated by the conventional vocal tract, and the proposed feature are fused by the MCE-Based score combination method to find the optimal speaker. The experimental results showed that the proposed feature vectors contained valid information to recognize the speaker. In addition, when speaker recognition is performed by combining the MCE-based multiple feature parameter scores, the recognition system outperformed the conventional one, particularly in low Gaussian mixture cases.