• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.649-654
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• 2002

The essential philosophy of the QFT(Quantitative Feedback Theory) is that a suitable controller can be found by loop shaping a nominal loop transfer function such that the frequency response of this function does not violate the QFT bounds. The loop shaping synthesis involves the identification of a structure and its specialization by means of the parameter optimization. This paper presents an optimization algorithm to estimate the controller parameters from the frequency transfer function synthesis using the TLS(Total Least Squares) in the QFT loop shaping procedure. The proposed method identifies the parameter vector of the robust controller from an overdetermined linear system developed from rearranging the two dimensional system matrices and output vectors obtained from the QFT bounds. The feasibility of the suggested algorithm is illustrated with an example.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.524-526
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• 1999

In the construction of successful fuzzy models and/or controllers for nonlinear systems, the identification of a good fuzzy inference system is an important yet difficult problem, which is traditionally accomplished by a time-consuming trial-and-error process. In this paper, we propose a systematic identification procedure for complex multi-input single-output nonlinear systems with DNA coding method. A DNA coding method is optimization algorithm based on biological DNA as conventional genetic algorithms(GAs) are. The strings in the DNA coding method are variable-length strings, while standard GAs work with a fixed-length coding scheme. the DNA coding method is well suited to learning because it allows a flexible representation of a fuzzy inference system. We also propose a new coding method fur applying the DNA coding method to the identification of fuzzy models. This coding scheme can effectively represent the zero-order Takagi-Sugeno(TS) fuzzy model. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a Duffing-forced oscillation system.

• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.6-10
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• 2020

Unlike modern photography technology, in the early days, efforts to physically compose an image with a concept similar to the current photograph have not been popular or commercially successful. The limitation of the use of images as artistic media or recordings has reached the stage of introducing the technology of image analysis to automate the function that humans recognize and judge through vision. In addition, the accuracy of the image has exceeded the human visual ability, enabling the technology that enables the step of recognizing and informing the fact that the human is not aware of it. Based on such a base, the range that can be applied through the image data in the future era can be said to be unpredictable, and the technology that targets large scale image database instead of an image is also expanding the possibilities as a new application technology. In order to identify a particular image from a massive database, different methodologies have been introduced. In this paper, we discuss image identifier production methods based on multi-resolution pyramid.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.216-223
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• 2003

A time-domain system identification (SI) method is developed for seismic damage assessment on structures. SI algorithms for complete measurements with respect to degrees-of-freedom are proposed. To take account of nonlinear dynamic response, an equation error in the incremental dynamic governing equation is defined for complete measurement between measured and computed acceleration. Variations of stiffness and damping parameters during earthquake vibration are chased by utilizing a constrained nonlinear optimization tool available in MATLAB. A simulation study has been carried out to identify damage event and to assess damage severity by using measured acceleration time history. Mass properties are assumed as known a priori. The effects of measurement noise on the identification are also investigated.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.201-203
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• 2007

The paper concerns the successive optimization for structure and parameters of fuzzy inference systems that is based on parallel Genetic Algorithms (PGA) and information data granulation (IG). PGA is multi, population based genetic algorithms, and it is used tu optimize structure and parameters of fuzzy model simultaneously, The granulation is realized with the aid of the C-means clustering. The concept of information granulation was applied to the fuzzy model in order to enhance the abilities of structural optimization. By doing that, we divide the input space to form the premise part of the fuzzy rules and the consequence part of each fuzzy rule is newly' organized based on center points of data group extracted by the C-Means clustering, It concerns the fuzzy model related parameters such as the number of input variables to be used in fuzzy model. a collection of specific subset of input variables, the number of membership functions according to used variables, and the polynomial type of the consequence part of fuzzy rules, The simultaneous optimization mechanism is explored. It can find optimal values related to structure and parameter of fuzzy model via PGA, the C-means clustering and standard least square method at once. A comparative analysis demonstrates that the Dnmosed algorithm is superior to the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.3
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• pp.123-128
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• 2017

Electric utilities has been considered the necessity to introduce AM(asset management) of electric power facilities in order to reduce maintenance cost of existing facilities and to maximize profit. In order to make decisions in terms of repairs and replacements for power transformers, not only measuring by counting parts and labor costs, but comprehensive comparison including reliability and cost is needed. Therefore, this study is modeling input cost for power transformer during its entire life and also the life cycle cost (LCC) technique is applied. In particular, this paper presents an application of heuristic harmony search(HS) optimization algorithm to the convergence and the validity of economic life assessment of power transformer from LCC technique. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. The effectiveness of the proposed identification method has been demonstrated through an economic life assessment simulation of power transformer using HS optimization algorithm.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.43-50
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• 2008

Multinomial logistic regression is a well known multiclass classification method in the field of statistical learning. More recently, the development of sparse multinomial logistic regression model has found application in microarray classification, where explicit identification of the most informative observations is of value. In this paper, we propose a sparse multinomial kernel logistic regression model, in which the sparsity arises from the use of a Laplacian prior and a fast exact algorithm is derived by employing a bound optimization approach. Experimental results are then presented to indicate the performance of the proposed procedure.

• Transactions of the Korean Society of Automotive Engineers
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• v.1 no.1
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• pp.120-130
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• 1993

In the analysis of automobile exhaust system, the exciting forces from the engine determine the dynamic behavior of the system and the dynamic characteristics influence the riding quality. Therefore, the identification of the force in numeric value is quite important for the vibrational reduction. However, the value is difficult to obtain by experiments due to harsh conditions around the engine. In this research, an optimization technology is adopted to evaluate the exciting forces. An experimental method is conducted for the verification of the finite element modeling. Displacements on the end of the exhaust system are measured under the idling environment. cost function is set up to minimize the differences between the displacements of the numerical simulation and the experiment. Design variables are the components of the exciting forces. That is, optimization is utilized to estimate the forces with existing data. Excellent estimations have been calculated efficiently and the information is used again for the forced vibration of the exhaust system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1988.10a
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• pp.55-60
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• 1988

This paper concentrates on the development of simplified and effective algorithm for optimum reinforced concrete(RC) member design. After constructing the data base of predetermined RC sections which are arranged in the order of increasing resistant capacity. Then, the relationship between the section identification numbers and resistant capacities of sections is estabilished by regression and it can be used to obtain the initial solution(section) which satisfies the design constraints imposed. Assuming that there exists the optimum section near the initially selected one, the direct search is conducted to find the discrete optimum solution. The optimization of the entire structure is accomplished through the individual member optimization.

• Computational Structural Engineering
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• v.2 no.1
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• pp.79-86
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• 1989

This paper concentrates on the development of simplified and effective algorithm for optimum reinforced concrete(RC) member design. After constructing the data base of predetermined RC sections which are arranged in the order of increasing resistant capacity, the relationship between the section identification numbers and resistant capacities of sections is estabilished by regression and it can be used to obtain the initial solution(section) which satisfies the design constraints imposed. Assuming that there exists the optimum solution. The optimization of the entire structure is accomplished through the individual mumber optimization.