• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1309-1317
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• 2012

Stochastic weather generators are commonly used to simulate time series of daily weather, especially precipitation amount. Recently, a generalized linear model (GLM) has been proposed as a convenient approach to fitting these weather generators. In this paper, a stochastic weather generator is considered to model the time series of daily precipitation at Seoul in South Korea. As a covariate, global temperature is introduced to relate long-term temporal scale predictor to short-term temporal predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate time series of seasonal total precipitation in the GLM weather generator as covariates. It is veri ed that the addition of these covariates does not distort the performance of the weather generator in other respects.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.623-625
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• 1998

This paper focuses on the fast convergence in nonlinear parameter optimization which is necessary for the fitting of nonlinear models to data. The simulated annealing(SA) and genetic algorithm(GA), which are widely used for combinatorial optimization problems, are stochastic strategy for search of the ground state and a powerful tool for optimization. However, their main disadvantage is the long convergence time by unnecessary extra works. It is also recognised that gradient-based nonlinear programing techniques would typically fail to find global minimum. Therefore, this paper develops a modified SA which is the SDS(Stochastic deterministic stochastic) algorithm can minimize cost function of optimal problem.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.4
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• pp.1148-1159
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• 2014

Different procedures for estimation of the extreme global wave hydroelastic responses in ships are discussed. Firstly, stochastic procedures for application in detailed numerical studies (CFD) are outlined. The use of the First Order Reliability Method (FORM) to generate critical wave episodes of short duration, less than 1 minute, with prescribed probability content is discussed for use in extreme response predictions including hydroelastic behaviour and slamming load events. The possibility of combining FORM results with Monte Carlo simulations is discussed for faster but still very accurate estimation of extreme responses. Secondly, stochastic procedures using measured time series of responses as input are considered. The Peak-over-Threshold procedure and the Weibull fitting are applied and discussed for the extreme value predictions including possible corrections for clustering effects.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2989-2991
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• 2000

TS 퍼지 모델은, 복잡한 비선형 시스템을 효과적으로 표현할 수 있는 주요한 근사 모델 중 하나이다. TS 퍼지 모델링을 위한 기존의 학습 방법론들은 대부분 전역적 근사 오차를 최소화하는 것을 목적으로 하는데, 이러한 경우에는 결과로서 얻어지는 75 퍼지 모델의 국소모델들이 근사 대상 시스템의 국소적 특성을 제대로 표현 할 수 없는 상황이 발생할 수 있다. 따라서 본 논문에서는 이러한 특성을 고려하여 새로운 학습 알고리즘을 제시함으로써 전역 지역적 성능을 동시에 향상시킬 수 있는 TS 퍼지 모델을 구하고자 한다 모델을 구하는데 있어서는 LMI를 이용한 풀이를 이용한다. 그리고 간단한 예제를 통하여 그 성능을 입증한다.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.457-458
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• 2007

This paper propose a method for representing distributed data of sensor networks. The proposed method is based on a general distributed regression framework that models sensor data by fitting a global function to each of the local measurements and explores the possible extensions of distribution regression by using complex signal representations. In order to reduce the amount of processed data and the required communication, the signal model has to be as compact as possible, with the ability to restore the arbitrary measurements. To achieve this requirement, data compression step is included, where the basis function set is changed to an overcomplete set. This have better advantages in case of nonstationary signal modeling than complete base representation.

• Journal of Power System Engineering
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• v.18 no.6
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• pp.45-50
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• 2014

In the previous paper, we have reported on the development of foaming sponge seat with the auxiliary spring member and suggested new possibility of the special seat with the auxiliary plastic member for movie theater chair. In this study, we have examined the major design parameters needed in the development of a foaming sponge seat in which the mesh type plastic member are inserted to improve the vibration transfer effect of a chair seat. Through analyzing several prototypes by applying experimentation as well as the experimental modal analysis method, it was confirmed that the effect of vibration transfer can be improved through the use of a mesh type plastic member and applied to the design of practical chair seat.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.334-334
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• 2018

에티오피아 Awash 하천유역의 수자원은 경제적, 사회적, 생태적으로 매우 중요하다. 하지만 이 지역에 신뢰성 높은 기상자료의 확보가 매우 어렵기 때문에 Climate Forecast System Reanalysis (CFSR)의 글로벌 기상자료를 이용한 수문성분해석결과와 기존의 제한된 기상자료를 활용한 결과를 비교하여 향후 두 자료를 적절히 활용하는 방안을 모색하였다. 수문모형은 글로벌 적용이 가능한 SWAT(Soil and Water Assessment Tool)을 활용하였고, 상이한 자료를 이용하여 구한 모형의 성능은 두 지점의 관측 유출량과의 비교를 통해 검토하였다. 매개변수의 보정은 Sequential uncertainty fitting (SUFI-2)방법을 이용하였다. Keleta 및 Melka Kunture 소유역에서의 유출량을 비교한 결과 기존의 가용 기상자료를 활용하여 구한 결과에 비해 CFSR 글로벌 기상자료를 이용한 결과가 보다 양호한 것으로 나타났다. 특히 유역면적이 Keleta소유역에 비해 6배가 큰 Melka Kunture 유역에서 CFSR 기상자료를 이용하여 산정한 유출량이 더욱 정확한 것으로 나타나 유역면적이 큰 곳에서 글로벌 자료의 활용성은 더욱 높은 것으로 확인되었다. 글로벌 기상자료의 활용은 아프리카의 대부분 지역과 같이 확보된 기상자료가 부족한 곳에서 유용하게 활용될 수 있을 것으로 전망되었다.

• Smart Structures and Systems
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• v.24 no.5
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• pp.659-668
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• 2019

In digital image correlation, speckle image is closely related to the measurement accuracy. A practical global evaluation criterion for speckle image is presented. Firstly, based on the essential factors of the texture image, both the average particle size and image sharpness are used for the assessment of speckle image. The former is calculated by a simplified auto-covariance function and Gaussian fitting, and the latter by focusing function. Secondly, the computation of the average particle size and image sharpness is verified by numerical simulation. The influence of these two evaluation parameters on mean deviation and standard deviation is discussed. Then, a physical model from speckle projection to image acquisition is established. The two evaluation parameters can be mapped to the physical devices, which demonstrate that the proposed evaluation method is reasonable. Finally, the engineering application of the evaluation method is pointed out.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.32.1-32.1
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• 2020

An independent determination of H0 is crucial given the growing tension of the Hubble constant (H0). In this work, we present a new determination of H0 using velocities and Tip of the Red Giant Branch (TRGB) distances to 33 galaxies in front of the Virgo Cluster. We model the infall pattern of the local Hubble flow modified by the Virgo mass, as a function of the H0, the radius of the zero-velocity surface R0, and the intrinsic velocity scatter. Fitting velocities and TRGB distances of 33 galaxies to the model, we obtain H0 = 65.6 +/- 3.4 (stat) +/- 1.0 (sys) km/s/Mpc and R0 = 6.96 +/- 0.35 Mpc. Our local H0 is consistent with the global H0 determined from cosmic microwave background radiation, showing no tension.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.63-73
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• 2011

The Pseudorange Corrections (PRC), which are used in DGPS as calibration messages, can contain outliers, noise, and anomalies, and these abnormal events are unpredictable. When those irregular PRC are used, the positioning error gets higher. In this paper, we propose a strategy of detecting and correcting outliers, noise, and anomalies by modeling the changing pattern of PRC through polynomial curve fitting techniques. To validate our strategy, we compared positioning errors obtained without PRC calibation with those with PRC calibration. As a result, we found that our algorithm performs very well; the horizontal RMS error was 3.84 m before the correction and 1.49 m after the correction.