• Korean Management Science Review
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• v.18 no.2
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• pp.117-124
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• 2001

This paper presents a machining parameter selection approach using an evolutionary computation (EC). In order to perform a successful material cutting process, the engineer is to select suitable machining parameters. Until now, it has been mostly done by the handbook look-up or solving optimization equations which is inconvenient when not in handy. The main thrust of the paper is to provide a handy machining parameter selection approach. The EC is applied to rapidly find optimal machining parameters for the user\\`s specific machining conditions. The EC is basically a combination of genetic a1gorithm and microcanonical stochastic simulated annealing method. The approach is described in detail with an application example. The paper concludes with a discussion on the potential of the proposed approach.

• Journal of the Korean Statistical Society
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• v.4 no.1
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• pp.67-78
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• 1975

Over twenty-five years ago, Professor Klein and Rubin presented the linear expenditure system. That system was first estimated by Stone. Subsequently many investigators have estimated that system. In this paper, many points of the error structure shown by Pollak and Wales are referred to. Barten presented an estimation theorem on a singular covariance matrix. In order to estimate parameters, we place an emphasis on the maximum likihood method which we believe to be most appropriate. As we have one linear restriction on parameters to be estimated, we maximized the associated likelihood function subject to that linear restriction through the well-known lagrange multiplier method. This paper is organized in the following fashion : (1) a brief description on classical consumer theory, (2) a linear expenditure system and its constraint, (3) dyanmic specification and stochastic specification, (4) estimation method, and (5) conclusion.

• Korean Journal of Hydrosciences
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• v.8
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• pp.125-136
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• 1997

The simulation techniques of hydrologic data series have develped for the purposes of the design of water resources system, the optimization of reservoir operation, and the design of flood control of reservoir, etc. While the stochastic models are usually used in most analysis of water resources fields for the generation of data sequences, the indexed sequential modeling (ISM) method based on generation of a series of overlapping short-term flow sequences directly from the historical record has been used for the data generation in the western USA since the early of 1980s. It was reported that the reliable results by ISM were obtained in practical applications. In this study, we generate annual inflow series at a location of Hong Cheon Dam site by using ISM method and autoregressive, order-1 model (AR(1)), and estimate the drought characteristics for the comparison aim between ISM and AR(1).

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1290-1294
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• 2004

In this study, new stochastic point rainfall models which can consider the correlation structure between rainfall intensity and duration are developed. In order to consider the negative and positive correlation simultaneously, the Gumbels type-II bivariate distribution is applied, and for the cluster structure of rainfall events, the Neyman-Scott cluster point process is selected. In the theoretical point of view, it is shown that the models considering the dependent structure between rainfall intensity and duration have slightly heavier tail autocorrelation functions than the corresponding independent mode]s. Results from generating long time rainfall events show that the dependent models better reproduce historical rainfall time series than the corresponding independent models in the sense of autocorrelation structures, zero rainfall probabilities and extreme rainfall events.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1437-1440
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• 2007

Many hydroclimatic time series are marked by interannual and longer quasi-period features that are associated with narrow band oscillatory climate modes. A time series modeling approach that directly considers such structures is developed and presented. The essence of the approach is to first develop a wavelet decomposition of the time series that retains only the statistically significant wavelet components, and to then model each such component and the residual time series as univariate autoregressive processes. The efficacy of this approach is demonstrated through the simulation of observed and paleo reconstructions of climate indices related to ENSO and AMO, tree ring and rainfall time series. Long ensemble simulations that preserve the spectral attributes of the time series in each ensemble member can be generated. The usual low order statistics are preserved by the proposed model, and its long memory performance is superior to the direction application of an autoregressive model.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.2
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• pp.177-190
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• 1996

구조물의 동적 응답 해석 문제에 대해서, 확률 유한요소법을 논의코자, 기조의 유한요소 해석법에 수반 변수법(adjoint variable approach)과 2차 섭동법(second order perturbation method)을 적용한다. 동적 민감도의 시간 응답을 고려하기 위해서 모든 시간에 대해서 갖는 구속 조건의 범함수 형태를 취하고, 시간 적분에 있어서 중첩법(fold superposition technique)에 근거를 둔 수치 해석이 훨씬 더 효과적임을 보인다. 본 논문의 확률 유한요소 해석법은 기존의 유한요소 해석법은 기존의 유한요소 코드에 맞추어 쉽게 적용할 수 있는 이점이 있음을 보이며, 이의 검정을 위해서, 2차원과 3차원 프레임 구조물에 대한 수치 해석을 하고 그 결과를 검토해 보았다.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.193-196
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• 1987

We reported that hot electron phenomena in submicron nMOSFET by Monte Carlo method. In order to predict the influence of the hot electron effects on the device reliability, either simple analytical model or a complete two dimensional numerical simulation has been adopted. Results of numerical simulation, based on the static mobility model, may be inaccurate when gate length of MOSFET is scaled down to less than 1um. Most of device simulation packages utilize the static nobility model. Monte Carlo method based on stochastic analysis of carrier movement may be a powerful tool to characterize hot electrons. In this work, energy and velocity distribution of carriers were obtained to predict the relative degree of short channel effects for different device parameters. Our analysis shows a few interesting results when $V_{ds}$ is 5 volt, average electron energy does not increase with gate bias as evidenced by substrate current.

• International Journal of Reliability and Applications
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• v.15 no.1
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• pp.65-76
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• 2014

In this article, a new model based on Lomax distribution is introduced. This new model is both useful and practical in areas such as economic, reliability and life testing. Some statistical properties of this model are presented including moments, hazard rate, reversed hazard rate, mean residual life and mean inactivity time functions, among others. It is also shown that the distributions of the new model are ordered with respect to the strongest likelihood ratio ordering. The method of moment and maximum likelihood estimation are used to estimates the unknown parameters. Simulation is utilized to calculate the unknown shape parameter and to study its properties. Finally, to illustrate the concepts, the appropriateness of the new model for real data sets are included.

• Journal of the Semiconductor & Display Technology
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• v.10 no.4
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• pp.71-77
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• 2011

This paper presents a production planning methodology for semiconductor manufacturing supply chain network with volatilities caused by uncertainties such as unstable demand and price. In order to take volatilities into account, we develop two approaches; 1) stochastic model with consideration of various cases and 2) deterministic model considering replanning cost, and propose efficient solution methods. Computational experiments show that the performance of the proposed method is superior to that of deterministic approach using various scenarios.

• Journal of the Korea Society for Simulation
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• v.10 no.2
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• pp.61-74
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• 2001

The reliability evaluation of the large scale network becomes very complicate according to the growing size of network. Moreover if the reliability is not constant but follows probability distribution function, it is almost impossible to compute them in theory. This paper studies the network evaluation methods in order to overcome such difficulties. For this an efficient path set algorithm which seeks the path set connecting the start and terminal nodes efficiently is developed. Also, various variance reduction techniques are applied to compute the system reliability to enhance the simulation performance. As a numerical example, a large scale network is given. The comparisons of the path set algorithm and the variance reduction techniques are discussed.