• Journal of Power Electronics
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• v.2 no.3
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• pp.155-161
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• 2002

This paper presents a maximum power point tracking algorithm for Photovoltaic array using only instantaneous output current information. The conventional Hill climbing method of peak power tracking has a disadvantage of oscillations about the maximum power point. To overcome this problem, we have developed an algorithm that will estimate the duty ratio corresponding to maximum power operation of solar cell. The estimation of the optimal duty ratio involves, finding the duty ratio at which integral value of output current is maximum. For the estimation, we have used the well know Lagrange's interpolation method. This method can track maximum power point quickly even for changing solar isolation and avoids oscillations after reaching the maximum power point.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.51-56
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• 2007

Feature functions were used for the classification of music. The spectral roll-off, variance, average peak level, and class were chosen to make up a feature function vector. Among these, it is the spectral roll-off function that has a low-frequency to high-frequency ratio. To find the optimal roll-off point, the roll-off points from 0.05 to 0.95 were swept. The classification success rate was monitored as the roll-off point was being changed. The data that were used for the experiments were taken from the sounds made by a modern violin and a baroque one. Their shapes and sounds are similar, but they differ slightly in sound texture. As such, the data obtained from the sounds of these two kinds of violin can be useful in finding an adequate roll-off point. The optimal roll-off point, as determined through the experiment, was 0.85. At this point, the classification success rate was 85%, which was the highest.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1448-1457
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• 2018

Many researchers devote themselves to develop model-predictive direct power control (MPDPC) so as to accelerate the response speed of the grid-connected systems, but they are troubled its large computing amount. On the basis of MPDPC, dual MPDPC (DMPDPC) is presented in this paper. The proposed algorithm divides the conventional MPDPC into two steps. In the first step, the optimal sector is obtained, which contains the optimal switching state in three-level converters. In the second step, the optimal switching state in the selected sector is searched to trace reference active and reactive power and balance neutral point voltage. Simulation and experiment results show that the proposed algorithm not only decreases the computational amount remarkably but also improves the steady-state performance. The dynamic response of the DMPDPC is as fast as that of the MPDPC.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.89-92
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• 2003

It is often that a large-scale linear programming(LP) problem may contain many constraints which are redundant or cause infeasibility on account of inefficient formulation or some errors in data input. Presolving or preprocessing is a series of operations which removes the underlying redundancy or detects infeasibility in the given LP problem. It is essential for the speedup of an LP system solving large-scale problems to implement presolving techniques. For the recovery of an optimal solution for the original problem from an optimal solution for the presolved problem, a special procedure, so called postsolving, must be applied. In this paper, we present how a postsolving procedure is constructed and implemented in LPABO, a interior-point based LP system. Briefly, all presolving processes are logged in a data structure in LPABO, and after the end of the solution method an optimal solution for the original problem is obtained by tracing the logs. In each stage of the postsolving procedure, the optimality of intermediate solutions is maintained. We tested our postsolving procedure on Netlib, Gondzio and Kennington LP data sets, and concluded that the computational burden of the procedure is relatively negligible compared with the total solving time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.295-305
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• 1993

The purpose of this study is to investigate the theoretical methodology for development of an water quality management system with the optimal control of dilution water and point sources in streams. For the development of objective function and constraints, the control vectors are defined with stream inflows and concentrations of effluents at water treatment plant, and the state vectors are defined with water quality parameters such as DO, $BOD_5$, COD and SS concentrations. The applied system solution technique is augmented Lagrangian technique. The developed water quality optimal management methodology was applied to a case study at the Musim stream in Cheong-ju city. The results of the application show that the methodology is suitable for the comprehensive analysis of polluted water systems, and will be utilized to more useful operation of limited water resources in Korean streams.

• Parasites, Hosts and Diseases
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• v.45 no.3
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• pp.239-243
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• 2007

Many allergists are currently focusing on the development of new diagnostic tools, and are attempting to improve both the sensitivity and specificity. A multiple allergen simultaneous test-chemiluminescent assay (MAST-CLA) is one of the most popular diagnostic tools used in the Republic of Korea. However, there remains controversy among allergists with regard to the cut-off point for a positive result. The present study was conducted in order to determine the validity of MAST-CLA as compared with that of the skin prick test, with particular emphasis on arthropod allergens, on the basis of percentage agreement rates and k-values, and also to suggest the optimal positive cutoff points using receiver operating characteristic (ROC) curves. The study was conducted with 97 subjects (54 men, 43 women). Optimal individual cut-off points were calculated as follows; class II for Dermatophagoides farinae, class I for Dermatophagoides pteronyssinus, and trace for a cockroach mix. These findings suggest that attempting to apply optimal individual cut-off points will be a good way of improving diagnostic tests, particularly MAST-CLA.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.4
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• pp.856-865
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• 1994

Cylindrical fine-ceramics, $Al_{2}O_{3}$, was lapped on its outer surface by vibrational lapping unit manufactured in the laboratory. Cylindrical lapping of fine-ceramics is necessarily be characterized and optimized because its process as other finishing methods is time-spending and, so, inefficient one, and because it is very complicated and random process affected by numerous factors in itself and in its environment. In this study, an efficient experimental approach, experimental design method, was used to analyze characteristics of the cylindrical lapping of fine-ceramics, $Al_{2}O_{3}$, and response surface methodology(RSM) to find out the optimal variables combination for the maximum improvement of surface roughness($R_a$). From the final surface roughness point of view in the given lapping conditions, a stationary point or optimal lapping conditions as well as the possible maximum improvement of surface roughness($R_a$) was predicted.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.53-63
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• 2013

To guide the decision making of the expert engineer specialized in power system operation and control; the practical OPF solution should take in consideration the critical situation due to severe loading conditions and fault in power system. Differential Evolution (DE) is one of the best Evolutionary Algorithms (EA) to solve real valued optimization problems. This paper presents simple Differential Evolution (DE) Optimization algorithm to solving multi objective optimal power flow (OPF) in the power system with shunt FACTS devices considering voltage deviation, power losses, and power flow branch. The proposed approach is examined and tested on the standard IEEE-30Bus power system test with different objective functions at critical situations. In addition, the non smooth cost function due to the effect of valve point has been considered within the second practical network test (13 generating units). The simulation results are compared with those by the other recent techniques. From the different case studies, it is observed that the results demonstrate the potential of the proposed approach and show clearly its effectiveness to solve practical OPF under contingent operation states.

• Journal of Drive and Control
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• v.12 no.4
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• pp.8-14
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• 2015

A quick-acting hydraulic fuse, which is mainly composed of a poppet, a seat, and a spring, must be designed to minimize the leaked oil volume during fuse operation on a line rupture. The optimal design parameters of a quick-acting hydraulic fuse were searched using the design of experiments method and the complex method. First, the $L_{50}(5^4)$ orthogonal array is used to find the robust minimum point among the 625 points of design variables. The search range can then be narrowed around the robust minimum point. Second, the $L_{25}(5^4)$ orthogonal array is used to obtain the variations of the design variables in the narrowed search range. The variations of design variables are used to set the structure of a polynomial equation representing the leakage oil volume of the quick-acting hydraulic fuse. The least squares method is then applied to obtain the coefficients of polynomial equation. Finally, the complex method is used to find the optimal design parameters where the objective function is described by the polynomial equation.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.515-518
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• 1998

This paper proposes a new hybrid algorithm for auto-tuning fuzzy controllers improving the performance. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a genetic-MGM algorithm. The object of the proposed algorithm is to promote search efficiency by a genetic and modified gradient optimization techniques. The proposed genetic and MGM algorithm is based on both the standard genetic algorithm and a gradient method. If a maximum point don't be changed around an optimal value at the end of performance during given generation, the genetic-MGM algorithm searches for an optimal value using the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algorithms. Simulation results verify the validity of the presented method.