• Journal of IKEEE
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• v.1 no.1 s.1
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• pp.19-30
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• 1997

In this paper we design the optimal satellite-tracking antenna $H{\infty}$ control system using genetic algorithms. To do this, we give gain and dynamics parameters to the weighting functions and apply genetic algorithms with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H{\infty}$ controller in the state space. These weighting functions and design parameter ${\gamma}$ are optimized simultaneously in the search domain guaranteeing the robust stability of closed-loop system. The effectiveness of this satellite-tracking antenna $H{\infty}$ control system is verified by computer simulation.

• Water for future
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• v.13 no.4
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• pp.41-50
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• 1980

The prupose of this study are the theoretical examination of Gamma distribution function and its application to hydraulic engineering, that is studying the simulation of monthly streamflow by the Gamma distribtution function model(Gamma Model) based on Monte Carlo technique. In the analysis, monthly streamflow data in the Nak Dong River, the Han River, and the Keum River were used and the data were changed to modular coefficient in order to make the analysis convenient. At first, the fitness of monthly streamflow to 2-Parameter Gamma distribution was tested by Chi-square and Kolmogrov-Smironov test, by which it was found the monthly streamflow were fit well to this Gamma distribution function. Then, the Gamma Model based on the Gamma distribution and Monte Carlo Method was used in the simulation of monthly streamflow, and simulateddata showed that all their stastical characteristics were preserved well in the simulation. Consequently, it can be concluded that the Gamma Model is suitable for the simulation of monthly streamflow series directly by using the Mote Carlo technique.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.1
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• pp.42-51
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• 2011

Poisson model and Gamma-Poisson model are popularly used to analyze statistical behavior from defective data. The methods are based on binary criteria, that is, good or failure. However, manufacturing industries prefer polytomous criteria for classifying manufactured products due to flexibility of marketing. In this paper, I introduce two multivariate Gamma-Poisson(MGP) models and estimation methods of the parameters in the models, which are able to handle polytomous data. The models and estimators are verified on defective pixels of LCD manufacturing. Experimental results show that both the independent MGP model and the multinomial MGP model have excellent performance in terms of mean absolute deviation and the choice of method depends on the purpose of use.

• Journal of Integrative Natural Science
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• v.7 no.2
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• pp.138-144
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• 2014

Fisher information matrix plays an important role in statistical inference of unknown parameters. Especially, it is used in objective Bayesian inference where we calculate the posterior distribution using a noninformative prior distribution, and also in an example of metric functions in geometry. To estimate parameters in a distribution, we can use the Fisher information matrix. The more the number of parameters increases, the more its matrix form gets complicated. In this paper, by using Mathematica programs we derive the Fisher information matrix for 4-parameter generalized gamma distribution which is used in reliability theory.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.437-444
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• 2015

In simulation-based circuit optimization, many simulation runs may be wasted while evaluating infeasible designs, i.e. the designs that do not meet the constraints. To avoid such a waste, this paper investigates the use of support vector machine (SVM) classifiers in predicting the design's feasibility prior to simulation and the optimal selection of the SVM parameters, namely, the Gaussian kernel shape parameter ${\gamma}$ and the misclassification penalty parameter C. These parameters affect the complexity as well as the accuracy of the model that SVM represents. For instance, the higher ${\gamma}$ is good for detailed modeling and the higher C is good for rejecting noise in the training set. However, our empirical study shows that a low ${\gamma}$ value is preferable due to the high spatial correlation among the circuit design candidates while C has negligible impacts due to the smooth and clean constraint boundaries of most circuit designs. The experimental results with an LC-tank oscillator example show that an optimal selection of these parameters can improve the prediction accuracy from 80 to 98% and model complexity by $10{\times}$.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.263-268
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• 2019

The $^3He$ proportional chamber is widely used for neutron measurement owing to its high neutron detection efficiency and simplicity for gamma-ray rejection. In general, the neutron and gamma-ray signals obtained from the $^3He$ proportional chamber can be easily separated by the difference in the pulse heights. However, for a high gamma-ray field, the gamma-ray signal cannot be precisely eliminated by the pulse height due to gamma-ray pulse pileup which causes the pulse height of gamma-ray pulse to increase and making the pulses due to neutrons and gamma rays indistinguishable. In this study, an improved algorithm for $n/{\gamma}$ discrimination using a parameter, which is the ratio of the rise time to the pulse height, is proposed. The $n/{\gamma}$ discrimination performance of the algorithm is evaluated by applying it to $^{252}Cf$ neutron signal separation from various gamma-ray exposure rate levels ranging 0.1-5 R/h. The performance is compared to that of the conventional pulse-height analysis method in terms of the gamma elimination ratio. The suggested algorithm shows better performance than the conventional one by 1.7% (at 0.1 R/h) to 70% (at 5 R/h) for gamma elimination.

• Journal of Korea Foundry Society
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• v.29 no.4
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• pp.181-186
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• 2009

The interrelationship between new parameter ${\sigma}$ and maximum diameter $D_{max}$ is elaborated and discussed in comparison with four other glass forming ability (GFA) parameters, i.e. (1) super-cooled liquid region ${\Delta}T_x (=T_x - T_g)$, (2) reduced glass transition temperature $T_{rg} (=T_g/T_l)$, (3) K parameter $K (=[T_x-T_g]/[T_l -T_x])$, and (4) gamma parameter ${\gamma}(=[T_x]/[T_l+T_g])$ in Ca-based bulk metallic glass (BMG) systems. The ${\sigma}$ parameter, defined as ${\Delta}T^*{\times}P^'$, has a far better correlation with $D_{max}$ than the GFA parameters suggested so far, clearly indicating that the liquid phase stability and atomic size mismatch dominantly affect the GFA of Ca-based BMGs. Thus, it can be understood that the GFA of BMGs can be properly described by considering structural aspects for glass formation as well as thermodynamic and kinetic aspects for glass formation.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.241-247
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• 2016

The tracking filter plays a key role in the accurate estimation and prediction of maneuvering a vessel's position and velocity when attempting to enhance safety by avoiding collision. Therefore, in order to achieve accurate estimation and prediction, many oceangoing vessels are equipped with the Automatic Radar Plotting Aid (ARPA) system. However, the accuracy of prediction depends on the tracking filter's ability to reduce noise and maintain a stable transient response. The purpose of this paper is to derive the optimal values of the gain parameters used in tracking a High Dynamic Warship. The algorithm employs a ${\alpha}-{\beta}-{\gamma}$ filter to provide accurate estimates and updates of the state variables, that is, positions, velocity and acceleration of the high dynamic warship based on previously observed values. In this study, the filtering coefficients ${\alpha}$, ${\beta}$ and ${\gamma}$ are determined from set values of the damping parameter, ${\xi}$. Optimization of the damping parameter, ${\xi}$, is achieved experimentally by plotting the residual error against different values of the damping parameter to determine the least value of the damping parameter that results in the optimum smoothing coefficients leading to a reduction in the noise corruption effect. Further investigation of the performance of the filter indicates that optimal smoothing coefficients depend on the initial and average velocity of the target.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.146-151
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• The Korean Journal of Applied Statistics
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• v.1 no.2
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• pp.27-33
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• 1987

Let $\Pi_i, \cdots, \Pi_k$ denote k gamma distributions with a common known shape parameter (degrees of freedom) r and scale parameters $\theta_1, \cdots, \theta_k$, respectively. Kim proposed an improved lower bound LB$(\delta^*)$, which concerns a two-stage elimimation type procedure for selecting the population associated with the largest scale parameter $max_{1\leqi\leqk} \theta_i$. The design constants (nr, mr, c) are given for k=4(1)10, $p^*=.95,.90 and \delta^*=1.75,2.0$. With these design constants, a comparison study was made with the procedure of Lee and Choi. As can be seen from the table, these are moderate amount of savings in the expected total sample size. Thus, together with the result in Lee and Choi, the two-stage procedure can perform much better than a single stage procedure.