• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.79-86
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• 2002

This paper proposes a new algorithm for estimating ARMA model parameters. In estimating ARMA model parameters, several methods such as generalized least square method, instrumental variable method have been developed. Among these methods, the utilization of a bootstrap type algorithm is known as one of the effective approach for the estimation, but there are cases that it does not converge. Hence, in this paper, making use of a cross correlation function and utilizing the relation of structural a priori knowledge, a new bootstrap algorithm is developed. By introducing theoretical relations, it became possible to remove terms, which is liable to include much noise. Therefore, this leads to robust parameter estimation. It is shown by numerical examples that using this algorithm, all simulation cases converge while only half cases succeeded with the previous one. As for the calculation time, judging from the fact that we got converged solutions, our proposed method is said to be superior as a whole.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.62-62
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• 1999

In this paper, we propose a new technique of estimating tail of steady-state queue length distribution; Pr(Q>q), fo ATM multiplexer. Pr(Q>q) is a fundamental measure of network congestion. Assessing Pr(Q>q) properly is crucial for design and control of ATM networks. Data traffic pattern of high-speed networks is highly correlated and bursty. Estimating Pr(Q>q) is very difficult because of correlation and burstiness. We estimate entropy(rate-function) using large deviation principles and threshold bootstrap. Simulation studies are conducted to compare the performance of an existing method and our new method.

• Geomechanics and Engineering
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• v.19 no.4
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• pp.343-352
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• 2019

For quality control and the economical design of grouted sand, the prior establishment of the unconfined compressive strength (UCS) estimating formula is very important. This study aims to develop an empirical UCS estimating formula for grouted sand based on the physical properties of sands and the UCS of cured pure grout. Four sands with varying particle sizes were grouted with both microfine cement and Ordinary Portland cement. Grouted specimens were prepared at three different relative densities and at three different water-to-cement ratios, and unconfined compression tests were performed. The results demonstrate that UCS of grouted sand can be expressed as the power function of the UCS of cured pure grout: $UCS_{grouted\;sand}/1MPa=A_{soil}{\cdot}(UCS_{pure}/1MPa)^N$. Because the exponent N strongly depends on the combination of pore area and pore size, N is expressed as the function of porosity (n) and specific surface ($S_a$). Additionally, because $S_a$ determines the area of the sand particle that cement particles can adsorb and n determines the number of cementation bondings between sand particles, $A_{soil}$ is also expressed as the function of n and $S_a$. Finally, the direct relationship between $A_{soil}$ and N is also investigated.

• Korean System Dynamics Review
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• v.15 no.3
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• pp.5-36
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• 2014

The purpose of this paper is to develop a System Dynamics model for estimating the volume of forest resources in the future and simulating the volume of function of public benefit linked to forest resources in dynamic manner. Also it is to analyze the impact when the volume of forest land conversion is controlled by policy using the SD model. The analysis was done at nation-wide for the simulation period 2000 to 2040. Estimated forest area was 6.2 million ha and estimated growing stock was $4.7\;billion\;m^3$ in 2040 from the future forecast without policies. Changing of forest resources, 13.9 billion tons of forest-ground-water storage was estimated, $1.8\;million\;m^3$ of erosion control of forest was estimated and 377 million tons of $CO_2$ absorption was estimated. As a result of simulation with two alternatives, forest area was less reduced and growing stock was bigger than do nothing policy. Also, function of public benefit reflected by changes of forest resources was enhanced. This study contributes to estimate the quantitatively measured volume of forest resources and function of public benefit over the 30 years in Korean forest land in scientific way. Using this SD model, decision maker would develop forest land policies more delicately for deserving forest resources and increasing the volume of function of public.

• Proceedings of the Acoustical Society of Korea Conference
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• 1984.12a
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• pp.100-106
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• 1984

Traditional methods for estimating the location of underwater target, i.e. the triangulation method and the wavefront curvature method, have been utilized. The location of a target is defined by the range and the bearing, which estimates can be obtained by evaluating the time delay between neighboring sensors. Many components of error occur in estimating the target range, among which the error due to the fluctuation of heading angle is outstanding. In this paper, the wavefront curvature method was used. We considered the error due to the heading fluctuation as the $\beta$-density process, from which we analized the range estimates with $\beta$-density function exist in some finite limits, and its mean value and variation are depicted as a function of true range and heading fluctuation. Given heading angles and sensor separation, maximum estimated heading errors are presented as a function of true range.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.219-228
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• 2004

In this paper we construct prediction intervals for nonlinear time series models using the bootstrap. We compare these prediction intervals to traditional asymptotic prediction intervals using quasi-score estimation function and M-quasi-score estimating function comprising bounded functions. Simulation results show that the bootstrap method leads to improved accuracy. The accuracy of the bootstrap is empirically demonstrated with the consumer price index.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1353-1360
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• 2008

An estimating procedure is introduced for the nonlinear mixed-effect Poisson regression, for longitudinal study, where data from different subjects are independent whereas data from same subject are correlated. The proposed procedure provides the estimates of the mean function of the response variables, where the canonical parameter is related to the input vector in a nonlinear form. The generalized cross validation function is introduced to choose optimal hyper-parameters in the procedure. Experimental results are then presented, which indicate the performance of the proposed estimating procedure.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.297-302
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• 2005

In this paper, an estimating damage on external surface of container using Capsize-Gaussian-Function (be called CGF) is presented. The estimation of the damage size can be get directly from two parameters of CGF, these are the depth and the flexure, also the direction of damage. The performance of the present method has been illustrated using an image of damage container, which had been taken from Hanjin Busan Port, after using image processing techniques to do preprocessing of the image, especially, the main used technique is Canny edge detecting that is widely used in computer vision to locate sharp intensity and to find object boundaries in the image, then correlation between the edge image from the preprocessing step and the CGF with three parameters (direction, depth, flexure), as a result, we get an image that perform damage information, and these parameters is an estimator directly to the damage.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.291-308
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• 2024

The current article discusses ratio type exponential estimators for estimating the mean of a finite population in sample surveys. The estimators uses robust regression's Huber M-estimation function, and their bias as well as mean squared error expressions are derived. It was campared with Kadilar, Candan, and Cingi (Hacet J Math Stat, 36, 181-188, 2007) estimators. The circumstances under which the suggested estimators perform better than competing estimators are discussed. Five different population datasets with a well recognized outlier have been widely used in numerical and simulation-based research. These thorough studies seek to provide strong proof to back up our claims by carefully assessing and validating the theoretical results reported in our study. The estimators that have been proposed are intended to significantly improve both the efficiency and accuracy of estimating the mean of a finite population. As a result, the results that are obtained from statistical analyses will be more reliable and precise.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.164-169
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• 1992

Classical methods for estimating transfer function models have not always been successful. A statistic approach to the identification of transfer function models which is corrupted by disturbances or noise is presented. The estimated impulse response is obtained from the autocorrelation function and cross correlation function between the measured input and output. Several data analysis tools such as R- , S- and GPAC array for the estimated impulse response give us pretty clear information on the order of transfer function models.