• Title/Summary/Keyword: 모델모수

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The Effects of Mass-size Relationship for Snow on the Simulated Surface Precipitation (눈송이의 크기와 질량 관계가 지표 강수 모의에 미치는 영향)

  • Lim, Kyo-Sun Sunny
    • Journal of the Korean earth science society
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    • v.41 no.1
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    • pp.1-18
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    • 2020
  • This study presented the effects of the assumed mass-size relationship for snow on the simulated surface precipitation by using cloud microphysics parameterizations in Weather Research and Forecasting (WRF) model. The selected cloud microphysics parameterizations are WRF Double-Moment 6-class (WDM6) and WRF Single-Moment 6-class (WSM6) in the WRF model. We replaced the mass-size relationship for snow in WDM6 and WSM6 with Thompson's mass-size relationship retrieved from measurement data. The sensitivity of the modified WDM6 and WSM6 was tested for the idealized 2-dimensional squall line and winter precipitation system over the Korean peninsula, respectively. The modified WDM6 and WSM6 resulted in the increase of graupel/rain mixing ratios and the decrease of snow mixing ratio in the low atmosphere. The changes of hydrometeor mixing ratio and surface precipitation could be due to the collision-coalescence process between raindrops and snow and the graupel melting process.

A study comparison of mortality projection using parametric and non-parametric model (모수와 비모수 모형을 활용한 사망률 예측 비교 연구)

  • Kim, Soon-Young;Oh, Jinho
    • The Korean Journal of Applied Statistics
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    • v.30 no.5
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    • pp.701-717
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    • 2017
  • The interest of Korean society and government on future demographic structures is increasing due to rapid aging. Korea's mortality rate is decreasing, but the declined gap is variable. In this study, we compare the Lee-Carter, Lee-Miller, Booth-Maindonald-Smith model and functional data model (FDM) as well as Coherent FDM using non-parametric smoothing technique. We are then examine a reasonable model for projecting on mortality declined rate trend in terms of accuracy of mortality rate by ages and life expectancy. The possibility of using non-parametric techniques for the prediction of mortality in Korea was also examined. Based on the analysis results, FDM and Coherent FDM, which uses the non-parametric technique and reflects the trend of recent data, are excellent. As a result, FDM and Coherent FDM are good fit, and predictability is also excellent assuming no significant future changes.

Bayesian Model based Korean Semantic Role Induction (베이지안 모형 기반 한국어 의미역 유도)

  • Won, Yousung;Lee, Woochul;Kim, Hyungjun;Lee, Yeonsoo
    • 한국어정보학회:학술대회논문집
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    • 2016.10a
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    • pp.111-116
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    • 2016
  • 의미역은 자연어 문장의 서술어와 관련된 논항의 역할을 설명하는 것으로, 주어진 서술어에 대한 논항인식(Argument Identification) 및 분류(Argument Labeling)의 과정을 거쳐 의미역 결정(Semantic Role Labeling)이 이루어진다. 이를 위해서는 격틀 사전을 이용한 방법이나 말뭉치를 이용한 지도 학습(Supervised Learning) 방법이 주를 이루고 있다. 이때, 격틀 사전 또는 의미역 주석 정보가 부착된 말뭉치를 구축하는 것은 필수적이지만, 이러한 노력을 최소화하기 위해 본 논문에서는 비모수적 베이지안 모델(Nonparametric Bayesian Model)을 기반으로 서술어에 가능한 의미역을 추론하는 비지도 학습(Unsupervised Learning)을 수행한다.

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A Study on the Lifetime Prediction of Device by the Method of Bayesian Estimate (베이지안 추정법에 의한 소자의 수명 예측에 관한 연구)

  • 오종환;오영환
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.8
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    • pp.1446-1452
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    • 1994
  • In this paper, Weibull distribution is applied to the lifetme distribution of a device. The method of Bayesian estimate used to estimate requiring parameter in order to predict lifetime of device using accelerated lifetime test data, namely failure time of device. The method of Bayesian estimate needs prior information in order to estimate parameter. But this paper proposed the method of parameter estimate without prior information. As stress is temperature, Arrhenius model is applied and the method of linear estimate is applied to predict lifetime of device at the state of normal operation.

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Bayesian Model based Korean Semantic Role Induction (베이지안 모형 기반 한국어 의미역 유도)

  • Won, Yousung;Lee, Woochul;Kim, Hyungjun;Lee, Yeonsoo
    • Annual Conference on Human and Language Technology
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    • 2016.10a
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    • pp.111-116
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    • 2016
  • 의미역은 자연어 문장의 서술어와 관련된 논항의 역할을 설명하는 것으로, 주어진 서술어에 대한 논항 인식(Argument Identification) 및 분류(Argument Labeling)의 과정을 거쳐 의미역 결정(Semantic Role Labeling)이 이루어진다. 이를 위해서는 격틀 사전을 이용한 방법이나 말뭉치를 이용한 지도 학습(Supervised Learning) 방법이 주를 이루고 있다. 이때, 격틀 사전 또는 의미역 주석 정보가 부착된 말뭉치를 구축하는 것은 필수적이지만, 이러한 노력을 최소화하기 위해 본 논문에서는 비모수적 베이지안 모델(Nonparametric Bayesian Model)을 기반으로 서술어에 가능한 의미역을 추론하는 비지도 학습(Unsupervised Learning)을 수행한다.

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Development of Life Test Methods for Assessment of Escalator Steps and Moving Walk Pallets (에스컬레이터 스텝 및 수평보행기 팰릿의 수명시험방법 개발)

  • Lim, Chang-Keun;Won, Min-Ho;Kang, In-Goo;Park, Jung-Won;Han, Jung-Keol
    • Proceedings of the Korean Reliability Society Conference
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    • 2006.05a
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    • pp.149-157
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    • 2006
  • 에스컬레이터 스텝 및 수평보행기 팰릿의 가속수명시험 국제 기준인 5백만회 시험조건 및 하중조건의 등가 현장 수명에 대한 근거를 산출하였다. 업체 및 산기원의 시험 데이터로부터 Weibull 모델을 추정하여 분석한 결과 에스컬레이터 스텝 및 수평보행기 팰릿의 형상모수가 각각 2.4$\sim$2.6 및 2.7$\sim$2.8로 산출되었다. 이 형상모수를 이용하여 본 연구에서 대상으로 한 에스컬레이터 스텝 및 수평보행기 팰릿의 B$_{10}$ 수명이 각각의 목표 수명 7년과 6년을 보증할 수 있음을 확인하였다.

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복권형 투자

  • Gang, Won
    • 한국벤처창업학회:학술대회논문집
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    • 2022.11a
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    • pp.237-240
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    • 2022
  • 창업기업은 ICO나 크라우드펀딩 등을 통해 소액주주로부터 자금을 조달하여 캐즘(chasm)을 무사히 통과하게 되면 전문투자기관으로부터 시리즈 투자를 유치하게 된다. 이는 시리즈 단계에서는 창업기업의 불확실성을 줄여주는 전문투자기관이 필요한 반면, 사업의 불확실성이 더 높은 캐즘단계에서는 전문투자기관이 존재하지 않아도 소액투자자들의 모집이 가능하다는 역설이라 할 수 있다. 이러한 역설을 설명하기 위해 본 연구에서는 일반투자자들이 복권형투자(lottery-type investment)에 참여하고 있음을 가정하고, 이에 대한 이론적인 고찰을 시도하였다. 복권형투자는 수익률의 분포가 높은 양의 왜도를 가질 때 이론적으로 가능하다. 사실 경제현상에서 정규분포를 찾아보긴 어렵고 왜도가 높은 파레토분포가 더 일반적이다. 정규분포에 기초한 기존의 가격모델은 오히려 특수해라고 할 수 있다. 기대효용이론에 기초한 복권형투자 모형은 실증분석을 통해 파레토분포의 형상모수(𝛼) 값이 먼저 추정되어야 설계가 가능하다.

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Development of Historical Data Selection Model Using Non-parametric test in Public Sector - focused on Reinforced Concrete Works of Multi-housing Projects - (비모수 검정기반 공공부문 실적단가 선정모델 개발 -공동주택 철근콘크리트 공종을 중심으로-)

  • Lee, Hyun-Ki;Jeon, Jae-Yong;Park, Sung-Chul;Hong, Tae-Hoon;Koo, Kyo-Jin;Hyun, Chang-Taek
    • Korean Journal of Construction Engineering and Management
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    • v.9 no.1
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    • pp.87-95
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    • 2008
  • The government wants to apply the construction cost estimating method based on historical data published in the first six months of 2004. Construction companies, however, require the proposed cost estimation model, to be improved which makes it difficult to predict a reasonable construction costs. This paper presents an improved historical data selection model after analyzing the problem of previous method throughout comparing contracted unit prices of reinforced concrete works selected by the previous model to market prices. The model which can select more feasible data would assist participates such as general contractors and sub-contractors to earn a proper profits.

Evaluation of Surface Wind Forecast over the Gangwon Province using the Mesoscale WRF Model (중규모 수치모델 WRF를 이용한 강원 지방 하층 풍속 예측 평가)

  • Seo, Beom-Keun;Byon, Jae-Young;Lim, Yoon-Jin;Choi, Byoung-Choel
    • Journal of the Korean earth science society
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    • v.36 no.2
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    • pp.158-170
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    • 2015
  • This study evaluates the wind speed forecast near the surface layer using the Weather Research Forecasting with Large Eddy Simulation (WRF-LES) model in order to compare the planetary boundary layer (PBL) parameterization with the LES model in terms of different spatial resolution. A numerical simulation is conducted with 1-km and 333-m horizontal resolution over the Gangwon Province including complex mountains and coastal region. The numerical experiments with 1-km and 333-m horizontal resolution employ PBL parameterization and LES, respectively. The wind speed forecast in mountainous region shows a better forecast performance in 333-m experiment than in 1-km, while wind speed in coastal region is similar to the observation in 1-km spatial resolution experiment. Therefore, LES experiment, which directly simulates the turbulence process near the surface layer, contributes to more accurate forecast of surface wind speed in mountainous regions.

Robust ridge regression for nonlinear mixed effects models with applications to quantitative high throughput screening assay data (비선형 혼합효과모형에서의 로버스트 능형회귀 방법과 정량적 고속 대량 스크리닝 자료에의 응용)

  • Yoo, Jiseon;Lim, Changwon
    • The Korean Journal of Applied Statistics
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    • v.31 no.1
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    • pp.123-137
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    • 2018
  • A nonlinear mixed effects model is mainly used to analyze repeated measurement data in various fields. A nonlinear mixed effects model consists of two stages: the first-stage individual-level model considers intra-individual variation and the second-stage population model considers inter-individual variation. The individual-level model, which is the first stage of the nonlinear mixed effects model, estimates the parameters of the nonlinear regression model. It is the same as the general nonlinear regression model, and usually estimates parameters using the least squares estimation method. However, the least squares estimation method may have a problem that the estimated value of the parameters and standard errors become extremely large if the assumed nonlinear function is not explicitly revealed by the data. In this paper, a new estimation method is proposed to solve this problem by introducing the ridge regression method recently proposed in the nonlinear regression model into the first-stage individual-level model of the nonlinear mixed effects model. The performance of the proposed estimator is compared with the performance with the standard estimator through a simulation study. The proposed methodology is also illustrated using quantitative high throughput screening data obtained from the US National Toxicology Program.