• International Journal of Quality Innovation
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• v.6 no.2
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• pp.105-115
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• 2005

In recent years, high-speed recording CD-R has already become the mainstream of CD-R market. Therefore, to promote the efficiency of recording CD-R is of significant importance. This study uses Taguchi's parameter design to improve the yield rate for the process of CD-R substrate. We have found 13 three-level controllable factors from the fishbone diagram, repeated 10 times the experiment with the L27(313) orthogonal array, and measured seven quality characteristics. We employ four general methods to find the optimal parameter conditions individually. Then, we perform the confirmation experiment and compare the results. Finally, we obtain the optimal parameter conditions. According to the analysis of benefits, the optimal parameter conditions can reduce the quality loss of CD-R substrate to about 21%. In the future, the results can be extended to other research of DVD-R substrate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.137-139
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• 2017

Modern manufacturing fields have been changed to use optimal manufacturing volume on the optimal demand prediction. This research is to compare the prediction capability of various prediction methods. And then, it is to suggest a flexible selection of the optimal prediction method according to optimal prediction capability.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.165-170
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• 2011

The Pfair scheduling algorithm, which is an optimal algorithm in the hard real-time multiprocessor environments, is based on the fixed quantum size. Recently, several methods that can determine the optimal quantum dynamically are developed in the mode change environments. These methods are based on the reach function and in many cases, we have to do the sequential search to find the optimal quantum. In this paper, we propose a new scheduling method, based on the improved reach function, that can determine the optimal quantum more quickly.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.97-99
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• 2003

This paper deals with optimal voltage regulation methods of line voltage regulator(SVR : Step Voltage Regulator) in power distribution systems. In order to deliver suitable voltages to as many customers as possible, the optimal sending voltage of SVR should be decided by the effective operation of voltage regulators at the distribution feeders and substations. In this paper, a new voltage regulation method based on the existing method is presented and an optimal coordination method of multiple voltage regulators is extended. The results from a case study show that the proposed methods can be a practical tool for the voltage regulation in distribution systems.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.365-373
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• 1999

Recently, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. In building neural network model, the selection of independent and dependent variables should be approached with great care and should be treated as a model construction process. Irrespective of the efficiency of a learning procedure in terms of convergence, generalization and stability, the ultimate performance of the estimator will depend on the relevance of the selected input variables and the quality of the data used. Approaches developed in statistical methods such as correlation analysis and stepwise selection method are often very useful. These methods, however, may not be the optimal ones for the development of neural network models. In this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables for neural network modeling. The proposed approach is demonstrated by applications to bankruptcy prediction modeling. Our experimental results show that this approach increases overall classification accuracy rate significantly.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.287-293
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• 2005

Predicting RNA secondary structure as accurately as possible is very important in functional analysis of RNA molecules. However, different prediction methods and related parameters including terminal GU pair of helices, minimum length of helices, and free energy systems often give different prediction results for the same RNA sequence. Then, which structure is more important than the others? i.e. which combinations of the methods and related parameters are the optimal? In order to investigate above problems, first, three prediction methods, namely, random stacking of helical regions (RS), helical regions distribution (HD), and Zuker's minimum free energy algorithm (ZMFE) were compared by taking 1139 tRNA sequences from Rfam database as the samples with different combinations of parameters. The optimal parameters are derived. Second, Zuker's dynamic programming method for prediction of RNA secondary structure was revised using the above optimal parameters and related software BJRNAFold was developed. Third, the effects of short-range interaction were studied. The results indicated that the prediction accuracy would be improved much if proper short-range factor were introduced. But the optimal short-range factor was difficult to determine. A user-adjustable parameter for short-range factor was introduced in BJRNAFold software.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.11-22
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• 2023

In this paper, we propose an efficient satellite selection method for multi-constellation GNSS. The number of visible satellites has increased dramatically recently due to multi-constellation GNSS. By the increased availability, the overall GNSS performance can be improved. Whereas, due to the increase of the number of visible satellites, the computational burden in implementing advanced processing such as integer ambiguity resolution and fault detection can be increased considerably. As widely known, the optimal satellite selection method requires very large computational burden and its real-time implementation is practically impossible. To reduce computational burden, several sub-optimal but efficient satellite selection methods have been proposed recently. However, these methods are prone to the local optimum problem and do not fully utilize the information redundancy between different constellation systems. To solve this problem, the proposed method utilizes the inter-system biases and geometric assignments. As a result, the proposed method can be implemented in real-time, avoids the local optimum problem, and does not exclude any single-satellite constellation. The performance of the proposed method is compared with the optimal method and two popular sub-optimal methods by a simulation and an experiment.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• Journal of Urban Science
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• v.7 no.1
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• pp.55-61
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• 2018

Long bridges, such as suspension bridges and diagonal bridges, are complex phenomena that show different behaviors depending on the shape and rigidity of the cross sections, such as wind vibrations and liquid vibrations from earthquakes in liquid storage containers. This is called the lower skirt on the lower side of the bridge, and the installation of lower skirt is effective for release and vortex vibrations caused by rapid winds, and that increases the stability of the wind resistance of the bridge. Optimal shape and installation of the lower skirt is also essential to make maximum wind speed effect of the lower skirt. Therefore, this study proposes a numerical analysis method to control the vibration of a bridge by calculating the optimal installation angle of an optimal lower skirt according to the optimal control theory and this study evaluates the impact on the optimal control system by minimizing the dominance equation with an evaluation function,which is an indicator for evaluating the optimal control theory state.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.743-752
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• 2002

The estimation of the response curve is the important problem in the quantal bioassay. When we estimate the response curve, we determine the design points in advance of the experiment. Then naturally we have a question of which design would be optimal. As a response curve estimator, locally weighted quasi-likelihood estimator has several more appealing features than the traditional nonparametric estimators. The optimal design density for the locally weighted quasi-likelihood estimator is derived and its ability both in theoretical and in empirical point of view are investigated.