• Journal of Korean Society of Steel Construction
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• v.10 no.3 s.36
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• pp.553-564
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• 1998

Recently, more and more steel-deck structural system for two story roads has been adopted as a solution against traffic congestion in urban area, mainly because of fast construction, reduced self-weight, higher stiffness and efficient erection compared to that of concrete decks. The main objective is to study on the unit-elective optimal type and proportioning of a rational steel-deck system for two story roads using an optimum design program specifically developed for steel-deck systems. The objective function for the optimization is formulated as a minimum cost design problem. The behavior and design constraints are formulated based on the ASD(Allowable Stress Design) criteria of the Korean Bridge Design Code. The optimum design program developed in this study consists of two steps - the first step for the optimization of the steel box or plate girder viaducts, and the second step for the optimum design of the steel-decks with closed or open ribs. A grid model is used as a structural analysis model for the optimization of the main girder system, while the analysis of the deck system is based on the Pelican-Esslinger method. The SQP(Sequential Quadratic Programming) is used as the optimization technique for the constrained optimization problem. By using a set of application examples, the rational type related to the optimized steel-deck system designs is investigated by comparing the cost effectiveness of each type. Based on the results of the investigation it may be concluded that the optimal linear box girder and deck system with closed ribs may be utilized as one of the most rational and economical viaducts in the construction of two-story roads.

• Structural Engineering and Mechanics
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• v.67 no.1
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• pp.33-43
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• 2018

The dynamic output-feedback robust control method based on linear matrix inequality (LMI) method is presented for suppressing vibration response of a functionally graded material (FGM) beam with piezoelectric actuator/sensor layers in this paper. Based on the reduced model obtained by using direct mode truncation, the linear fractional state space representation of a piezoelectric FGM beam with material properties varying through the thickness is developed by considering both the inherent uncertainties in constitution material properties as well as material distribution and the model error due to mode truncation. The dynamic output-feedback robust H-infinity control law is implemented to suppress the vibration response of the piezoelectric FGM beam and the LMI method is utilized to convert control problem into convex optimization problem for efficient computation. In numerical studies, the flexural vibration control of a cantilever piezoelectric FGM beam is considered to investigate the accuracy and efficiency of the proposed control method. Compared with the efficient linear quadratic regulator (LQR) widely employed in literatures, the proposed robust control method requires less control voltage applied to the piezoelectric actuator in the case of same control performance for the controlled closed-loop system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.5
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• pp.179-189
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• 2008

The object of this study is to develope a program with proposed numerical techniques for an optimal seismic control of structures using active tendon systems. Ricatti closed-loop algorithm has been applied to control the active tendon systems with time-delay problem. The optimal control is formulated as an optimization problem which is finding optimal weighting matrices by minimizing the quadratic performance index by SUMT. In order to find the optimal location of active tendons in structures, controllability index has been introduced. From numerical examples, the current optimal control technique with optimal location of tendons was suitable to control the seismic response of structures.

• Journal of the Korea Society of Computer and Information
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• v.15 no.7
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• pp.11-17
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• 2010

This paper proposes an improved SMO solving a quadratic optmization problem for class imbalanced learning. The SMO algorithm is aproporiate for solving the optimization problem of a support vector machine that assigns the different regularization values to the two classes, and the prosoposed SMO learning algorithm iterates the learning steps to find the current optimal solutions of only two Lagrange variables selected per class. The proposed algorithm is tested with the UCI benchmarking problems and compared to the experimental results of the SMO algorithm with the g-mean measure that considers class imbalanced distribution for gerneralization performance. In comparison to the SMO algorithm, the proposed algorithm is effective to improve the prediction rate of the minority class data and could shorthen the training time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.243-250
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• 2014

In this paper, I devise a balance-swap optimization (BSO) algorithm to solve economic load dispatch with a quadratic fuel cost function. This algorithm firstly sets initial values to $P_i{\leftarrow}P_i^{max}$, (${\Sigma}P_i^{max}$ > $P_d$) and subsequently entails two major processes: a balance process whereby a generator's power i of $_{max}\{F(P_i)-F(P_i-{\alpha})\}$, ${\alpha}=_{min}(P_i-P_i^{min})$ is balanced by $P_i{\leftarrow}P_i-{\alpha}$ until ${\Sigma}P_i=P_d$; and a swap process whereby $_{max}\{F(P_i)-F(P_i-{\beta})\}$ > $_{min}\{F(P_i+{{\beta})-F(P_j)\}$, $i{\neq}j$, ${\beta}$ = 1.0, 0.1, 0.1, 0.01, 0.001 is set at $P_i{\leftarrow}P_i-{\beta}$, $P_j{\leftarrow}P_j+{\beta}$. When applied to 15, 20, and 38-generators benchmark data, this simple algorithm has proven to consistently yield the best possible results. Moreover, this algorithm has dramatically reduced the costs for a centralized operation of 73-generators - a sum of the three benchmark cases - which could otherwise have been impossible for independent operations.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.5
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• pp.592-600
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• 2014

This paper proposes an enhanced adaptive genetic algorithm(EAGA) dedicated to pattern synthesis of array antenna which conforms to a curved surface of rotation with quadratic function. EAGA combines adaptive genetic algorithm(AGA) with invasive weed optimization(IWO) for the faster convergence and the lower cost value of the cost function. The amplitude and phase of each excited weighting factor are optimized to meet the required goals using EAGA. The EAGA results indicate that the proposed algorithm is superior to AGA when applied to the problem of conformal array antenna pattern synthesis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.602-610
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• 2018

The model predictive control is an effective method to optimize the current control input that predicts the current control state and the future error using the predictive model of the control system when the reference trajectory is known. Since the control input can not have a physically infinitely large value, a predictive controller design with constraints should be considered. In addition, the reference model $A_r$ and the weight matrices Q, R that determine the control performance of the predictive controller are not optimized as arbitrarily designated should be considered in the controller design. In this study, we construct a predictive controller of a mobile robot by transforming it into a quadratic programming problem with constraints, The control performance of the mobile robot can be improved by optimizing the control parameters of the predictive controller that determines the control performance of the mobile robot using genetic algorithm. Through the computer simulation, the superiority of the proposed method is confirmed by comparing with the existing method.

• Computational Structural Engineering
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• v.1 no.1
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• pp.87-94
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• 1988

The linerization method as one of the recursive quadratic programming method is applied for the optimal design of a large-scale structure supported by Pshenichny's proof of global convergence of the algorithm and convergence rate estimates. The linearization method transforms all constants of the design problem into an equivalent linearized constraint and employs the active-set strategy. This results in substantial computational savings by reducing the number of sate and adjoint to be solved at every design iteration. The illustrative example of plates with beams supported by columns is the typical one of a large-scale structure to give successful optimum solutions with satisfactory convergence criteria. Hopefully, the method may be applicable to all classes of optimization problems.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.708-710
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• 2004

This paper studies a multirate sampled-data control for LTI systems by using the digital redesign (DR) method. In this note, to well tackle the problem associated with both the state matching and the stabilization, our nobel strategy is to minimize the linear quadratic cost function. The main features of the proposed method are that i) the delta-operator-based descretization method is applied to improve the state-matching performance in the fast sampling limit and/or the large input multiplicity; ii) the proposed multirate control scheme can improve the state-matching performance in the long sampling limit; iii) some sufficient conditions that guarantee the stability of the closed-loop discrete-time system and provide a guarantee cost for the cost function can be formulated in the LMIs format; and iv) an optimal sampled-data controller in the sense of minimizing the upper bound of the cost function is also given by means of an LMI optimization procedure.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.8
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• pp.398-402
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• 2002

The ELD computation has been based upon the so-called B-coefficient which uses a quadratic approximation of system loss as a function of generation output. Direct derivation of system loss sensitivity based on the Jacobian-based method was developed in early 1970s', which could eliminate the dependence upon the approximate loss formula. However, both the B-coefficient and the Jacobian-based method require a complicated Procedure for calculating the system loss sensitivity included in the constraints of the optimization problem. In this paper, an ELD formulation in which only the bus power equations are defined as the constraints has been introduced. Derivation of the partial derivatives of the system loss with respect to the generator output and calculation of the penalty factors for individual generators are not required anymore in proposed method. A comprehensive solution procedure including calculation of the Jacobians and Hessians of the formulation has been presented in detail. Proposed ELD formulation has been tested on a sample system and the simulation indicated a satisfactory result.