• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.6-11
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• 2005

In this paper, we propose a new fuzzy clustering scheme that optimizes the initial structure and the parameters to improve the performance of a intelligent systems. The proposed method keeps the good properties of clustering, and improves the total systems' performance at the same time, Especially, the proposed algorithm not only keeps robust to change threshold value in the optimization process, but also improves the performance of a system through the process of the self-organizing and the converging intelligent systems in its structure of cluster. In experiments, the superiority of the proposed scheme is presented by comparing its performance with other methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.603-610
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• 2001

Industrial processes are normally operated by skilled humans who have the cumulative and logical information about the system. Fuzzy control has been investigated for many application. Intelligent control approaches based on fuzzy logic have a chance to include human thinking. This paper represents modeling approach based upon operators knowledge without mathematical model of the system and optimize the controller. The experimented system is constructed for sending a ball to the goal position using wind of two DC motors in the predefined path. A vision camera to mimic human eyes detects the ball position. The system used in this experiment could be hardly modeled by mathematical methods and ould not be easily controlled by conventional manners. The controller is designed based on the input-output data and experimental knowledge obtained by trials, and optimized under the predefined performance criterion. And this paper shows the data adaptation for changeable operating condition. When the system is driven in the abnormal condition with unconsidered noise, the new optimal operating parameters could be defined by adjusting membership functions. Thus, this technique could be applied in industrial fields.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.432-441
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• 2000

This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Genetic algorithm has been used to identifY parameters and structure of fuzzy model because it has the ability to search optimal solution somewhat globally. The genetic algorithm, however, has a problem, which optimization process can be premature convergence in the case of lack of genetic divergence of population. Virus- evolutionary genetic algorithm(VEGA) could be a strategy against this local convergence. Therefore, we use VEGA for fuzzy modeling. In this method, local information is exchanged in population so that population can sustain genetic divergence. finally, to prove the theoretical hypothesis, we provide numerical examples to evaluate the feasibility and generality of fuzzy modeling using VEGA.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.355-361
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• 2009

This paper proposes a new basic unit level rate control algorithm which generates the output bits corresponding to the target bits. The H.264 standard uses various coding modes and optimization methods to improve the compression performance, which makes it difficult to control the generated traffic accurately. In the proposed scheme, the allocated bits to a frame are distributed to all basic units properly to encode each basic unit according to the bit budget. After encoding the frame, the encoding parameters are adjusted according to the difference between the target and the resulting values. It is shown by experimental results that the new algorithm can generate output bit rates accurately corresponding to the target bit rates with the PSNR performance better than that of the existing rate control algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.177-182
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• 2010

The forward convener is one of power supplies used widely. This paper presents parameter tuning methods to obtain optimal circuit element values for the forward converter to minimize the output voltage variation under various load changing environments. The conventional method using the concept of the phase margin is extended to have optimal phase margin that gives slightly improved performance in the output voltage response. For this, the phase margin becomes the tuning parameter and is optimized with the genetic algorithm. Next, the circuit element values are directly chosen as the tuning parameters and also optimized using the genetic algorithm to have very improved performance in the output voltage control of the forward converter.

• Journal of Information Display
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• v.12 no.4
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• pp.167-171
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• 2011

The angular distribution of the luminance on each optical component of 40-inch light-emitting diode backlight was measured and studied, using the optical-simulation method. Several scattering functions were investigated as the reflection distribution function of the scattering dots printed on the bottom surface of the light guide plate (LGP). It was found that both the diffuse Lambertian and near-specular Gaussian scattering functions were necessary for the successful reproduction of the experimental angular distribution of the luminance. The optimization of the scattering parameters included in these scattering functions led to almost the same luminance distribution as that obtained from the experiment. This approach may be an effective way of indirectly estimating the reflection distribution function of the scattering dots of the LGP, which cannot be made accessible through any other experimental method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.3
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• pp.591-596
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• 1994

Threshold dependence on stripe width in gain-guided single quantum well lasers has been examined by complex domain effective index method. It is found, in narrow stripe regime, that the lateral optical confinement estimated by newly introduced parameters decreases very rapidly as the transverse optical confinement factor decreases. Thus, in a single quantum well laser with a usually very small, the optical confinement may become very poor depending on stripe width not only in the transverse but also in the lateral direction, further enhancing the gain saturation and often leading to an anomalously high threshold current. The understanding of rather anomalous threshold dependence on stripe width will be very important in optimization of quantum well laser diode structure.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07a
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• pp.67-73
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• 2002

The development of high performance HTS wire is a key factor for various electrical applications of coils and cables. The purpose of this paper is to review and consider the main manufacturing technologies of HTS wire and its current status. A lot of efforts have been focused on the optimization of PIT parameters for Bi-2223/Ag wire. According to this, long Bi-2223 wires having Ic of 130 A were recently produced and their mass production has been underway in US. The current status performance of Bi-2223 wire is supposed to be used in power transmission cable because of its lower self-field property. Y-123 second generation conductor is extensively being developed throughout the world and many fabrication processes are competed with each other. 30 m-long Y-123 wire with Ic of 0.8 MA/$\textrm{cm}^2$ was recently fabricated using IBAD and PLD techniques in Japan. This result offers promise of scalable processing of practical multi-layer coated conductor.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.152-154
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• 2005

In this paper, we propose a new architecture of Fuzzy Polynomial Neural Networks(FPNN) by means of genetically optimized Fuzzy Polynomial Neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially Genetic Algorithms(GAs). The design of the network exploits the extended Group Method of Data Handling(GMDH) with some essential parameters of the network being provided by the designer and kept fixed throughout the overall development process. This restriction may hamper a possibility of producing an optimal architecture of the model. The proposed FPNN gives rise to a structurally optimized network and comes with a substantial level of flexibility in comparison to the one we encounter in conventional FPNNs. It is shown that the proposed genetic algorithms-based Fuzzy Polynomial Neural Networks is more useful and effective than the existing models for nonlinear process. We experimented with Medical Imaging System(MIS) dataset to evaluate the performance of the proposed model.

• International Journal of Concrete Structures and Materials
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• v.2 no.2
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• pp.161-167
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• 2008

Optimization of concrete mixing system is very important for the production of quality mixture of concrete and requires very complicated, specialized knowledge as there are a variety of variables that influence the result. One of the methods of optimizing the concrete mixing system is to minimize the volume of cement paste which, in turn, means maximizing the volume of aggregate. The purpose of this study is to determine the minimum volume of cement paste used in the design of concrete mixture and to design the optimum concrete mixing system based on the fluidity of mortar and concrete. In determining the minimum volume of cement paste, experiments of mortar and concrete were performed based on their workability, material segregation and bleeding. Type of aggregate, granularity distribution and sand percentage were used as test parameters and measurements were taken of the distribution of granularity, usage of HRWRA, minimum volume of paste and drying shrinkage and compressive strength of concrete.