• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.101-110
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• 2002

This study first explains general features of traffic assignment models and network loading methods, and investigates the relationship between them. Then it introduces a dynamic network loading method, which accounts far time variable additionally. First of all, this study suggests that it is important to consider some requirements for the dynamic network loading, such as causality, FIFO(First-In-First-Out) discipline, the flow propagation, and the flow conservation. The details of dynamic network loafing methods are explained in the form of algorithm, and numerical examples are shown in the test network by adopting deterministic queuing model for a link Performance function.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.04a
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• pp.13-18
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• 1992

구조물의 동적실험을 통하여 얻은 하중과 거동에 대한 시간기록을 분석하여, 구조계의 동 특성계수들을 추정하는 기법에 대하여 연구하였다. 실험과정 및 해석모형과정의 오차를 고려하기 위하여, 하중기록과 구조거동기록간의 관계를 추계론적 자동회기 및 이동평균모형(Stochastic Auto-Regressive and Moving-Average (ARMAX) Model)음 사용하여 모형화하였다. 미지의 ARMAX 계수행렬들은 순차적 예측오차기법을 사용하여 추정하였으며, 계수추정기법의 효율성을 증진시키기 위하여, Exponential Data Weighting, Global Data Weighting 및 Square Root Estimation 기법을 활용하였다. 다중거동측정계의 예제해석을 통하여 이의 효율성을 분석하였다.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.381-387
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• 2011

This paper suggests a method for estimating components of variance in one-factor random model. Estimates of variance components are given by the method of moments. Sums of squares due to variance sources are obtained by projections. This paper also shows how to use eigenvalues for getting the coefficients of variance components in the expression of the expectations of the mean squares. The suggested method shows easier and faster than the method of Harley's synthesis.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.103-114
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• 2014

Significant research has been devoted to the consistency index of the Analytic Hierarchy Process(AHP) from several perspectives. Critics of the consistency index in AHP state that the critical value of consistency index depends on an average of the random index based simulation study using a 9 scale comparison matrix. We found that the distribution of the consistency index followed the skew distribution according to the dimension of the comparison matrix based on a simulation study with a 9 scale comparison matrix. From the simulation study, we suggest a consistency index quantile table to assist the decision-making process in AHP; in addition, we can approximate the distribution of the consistency index to the gamma distribution under the limited assumptions.

• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.19-26
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• 2024

The phase-type, PH, distribution is defined as the time to absorption into a terminal state in a continuous-time Markov chain. As the PH distribution includes family of exponential distributions, it has been widely used in stochastic models. Since the PH distribution is represented and generated by an initial probability vector and a generator matrix which is called the Markovian representation, we need to find a vector and a matrix that are consistent with given set of moments if we want simulate a PH distribution. In this paper, we propose an approach to simulate a PH distribution based on distribution function which can be obtained directly from moments. For the simulation of PH distribution of order 2, closed-form formula and streamlined procedures are given based on the Jordan decomposition and the minimal Laplace transform which is computationally more efficient than the moment matching methods for the Markovian representation. Our approach can be used more effectively than the Markovian representation in generating higher order PH distribution in queueing network simulation.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.581-594
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• 2016

We introduce innovations state space exponential smoothing models (ISS-ESM) that can analyze time series with multiple seasonal patterns. Especially, in order to control complex structure existing in the multiple patterns, the model equations use a matrix consisting of seasonal updating parameters. It enables us to group the seasonal parameters according to their similarity. Because of the grouped parameters, we can accomplish the principle of parsimony. Further, the ISS-ESM can potentially accommodate any number of multiple seasonal patterns. The models are applied to predict electricity demand in Korea that is observed on hourly basis, and we compare their performance with that of the traditional exponential smoothing methods. It is observed that the ISS-ESM are superior to the traditional methods in terms of the prediction and the interpretability of seasonal patterns.

• Water for future
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• v.25 no.4
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• pp.109-119
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• 1992

The purpose of this study is to develop real-time streamflow forecasting models in order to manage effectively the flood warning system and water resources during the storm. The stochastic system models of the rainfall-runoff process using in this study are constituted and applied the Recursive Least Square and the Instrumental Variable-Approximate Maximum Likelihood algorithm which can estimate recursively the optimal parameters of the model. Also, in order to improve the performance of streamflow forecasting, initial values of the model parameter and covariance matrix of parameter estimate errors were evaluated by using the observed historical data of the hourly rainfall-runoff, and the accuracy and applicability of the models developed in this study were examined by the analysis of the I-step ahead streamflow forecasts.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.263-273
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• 2010

Missing values in time series can be treated as unknown parameters and estimated by maximum likelihood or as random variables and predicted by the conditional expectation of the unknown values given the data. The purpose of this study is to impute missing values which are regarded as the maximum likelihood estimator and random variable in incomplete data and to compare with two methods using ARMA and STAR model. For illustration, the Mumps data reported from the national capital region monthly over the years 2001~2009 are used, and estimate precision of missing values and forecast precision of future data are compared with two methods.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.6 s.40
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• pp.55-66
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• 2004

Recently, many high-rise apartment buildings using the box system, composed of only reinforced concrete walls and slabs, have been constructed. In residential buildings such as apartments, vibrations occur from various sources and these vibrations transfer to neighboring residential units through walls and slabs. It is necessary to use a refined finite element model for an accurate vibration analysis of shear wall building structures. But it would take significant amount of computational time and memory if the entire building structure were subdivided into a finer mesh. Therefore, an efficient analytical method, which has only translational DOFs perpendicular to walls or slabs by the matrix condensation technique, is proposed in this study to obtain accurate results in significantly reduced computational time. If all of the DOFs except those perpendicular to walls or slabs in the shear wall structure eliminated using the matrix condensation technique at a time, the computational time for the matrix condensation would be significant. Thus, the modeling technique using super elements and substructuring technique is proposed to reduce the computational time for the matrix condensation. Dynamic analysis of 3-story and 5-story shear wall example structures were performed to verify the efficiency and accuracy of the proposed method. It was confirmed that the proposed method can provide the results with outstanding accuracy requiring significantly reduced computational time and memory.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.101-109
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• 2011

In most of the urbanized cities, socio-economic attributes tend to cluster as patterns of similarity in space, namely spatial autocorrelation, by agglomeration forces. The classical linear regression model, the most frequently adopted in the trip generation step, cannot sufficiently represent this effect. In order to take into account the effect properly, we need a model which adequately deals with the spatial dependence patterns. In this study, the Geographically Weighted Regression (GWR) model is adopted as an alternative method for the local analysis of relationships in multivariate data sets; that is GWR extends this traditional regression framework by estimating local rather than global parameters. This study shows the existence of spatial effects in the production and attraction of home base/non-home based trips through the GWR model using travel data collected in Daegu metropolitan area. Furthermore, LISA is employed to verify the fact that the local spatial autocorrelation exists.