• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.4
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• pp.199-204
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• 2005

In an electricity market with an imperfect competition, participants make plans of bidding and transaction strategies to maximize their own profits. The market price and the quantity are concerned with the operation reserve as well as the bidding system and demand curves in an electricity market. This paper presents a market model combined by an energy market and an operating reserve market. The competition of the generation producers in the combined market is formulated as a gaming of selecting bid parameters such as intersections and slopes in bid functions. The Nash Equilibrium(NE) is analyzed by using a hi-level optimization; maximization of Social Welfare(SW) and maximization of the producers' profits.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.145-154
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• 2020

Maximum likelihood (ML) is the best estimator asymptotically as the number of training samples approaches infinity. This paper deduces an adaptive algorithm for blind signal processing problem based on gradient optimization criterion. A parametric density model is introduced through a parameterized generalized distribution family in ML framework. After specifying a limited number of parameters, the density of specific original signal can be approximated automatically by the constructed density function. Consequently, signal separation can be conducted without any prior information about the probability density of the desired original signal. Simulations on classical biomedical signals confirm the performance of the deduced technique.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1429-1432
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• 2003

This paper addresses the problem of finding a constrained nearest neighbor for moving query point(we call it CNNMP) The Nearest neighbor problem is classified by existence of a constrained region, the number of query result and movement of query point and target. The problem assumes that the query point is not static, as 1-nearest neighbor problem, but varies its position over time to the constrained region. The parameters as NC, NCMBR, CQR and QL for the algorithm are also presented. We suggest the query optimization algorithm in consideration of topological relationship among them

• Journal of the Korean institute of surface engineering
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• v.50 no.6
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• pp.439-446
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• 2017

Plasma electrolyte oxidation (PEO) is a kind of anodization, in which a very high voltage or current is applied to a metal substrate in various electrolytes, allowing distinctly thick thickness of the oxide film with outstanding film properties, such as a good corrosion resistance, mechanical strength, thermal stability, and excellent adhesion to a substrate. Herein, we tried to find the optimal pretreatment conditions among commercially available solutions in order to produce PEO anodizing at relatively low voltage. We characterized the surface morphologies of the sample by scanning electron microscope (SEM), atomic force microscopy (AFM), and investigated color parameters of the pretreated surface of Ti by spectrophotometer.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1589-1590
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• 2006

A method to determine functional relationships between the variable physical dimensions of an antenna and the antenna performance characteristics is presented. By applying multi-expression programming (MEP) to this data set, optimization with regard to a given criteria can be subsequently performed on the functions instead of performing repealed electromagnetic simulations. The functionals are trained on an initial population of simulation samples and refined using a point-wise error estimate to identify design parameters for subsequent samples. Additionally, the depth of the MEP tree is adjusted for increased accuracy as the data set is deemed sufficient.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1110-1112
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• 1996

In this paper, we propose a new approach for robust auto-tuning of PID gains using Evolution Strategy. Evolution Strategy is searching algorithm which imitate the principles of natural evolution as a method to solve parameter optimization problem and easy to use without any other special mathematical theory. Through the simulation of the speed control of a series-connected de motor, our proposed method shows more improved performance by finding optimal parameters of PID controller than a classical Ziegler-Nichols method.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.166-168
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• 1996

This paper presents an power system optimization method which solves real and reactive power dispatch problems using evolutionary computation such as genetic algorithms(GAs), evolutionary programming(EP), and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most these approaches have the common defect of being caught to a local minimum solution. Recently, global search methods such as GAs, EP, and ES are introduced. The proposed methods, applied to the IEEE 30-bus system, were run for 12 other exogenous parameters. Each simulation result, by which evolutionary computations are compared and analyzed, shows the possibility of applications of evolutionary computation to large scale power systems.

• 한국연소학회:학술대회논문집
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• 2013.06a
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• pp.15-17
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• 2013

In the design of combined cycle power plants, the design parameters considered mainly could be changed and added for performance evaluation with change on the design objective and method. Therefore, the design criteria considering the different objectives and type of power plant were needed. Thermodynamic and economic analyses of various types of gas turbine combined cycle power plants with demand on generation of power and heat and carbon capture system from high pressure flue gas have been performed to establish criteria for optimization of power plants.

• Journal of the Korean Magnetic Resonance Society
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• v.24 no.1
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• pp.30-37
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• 2020

Quantitative nuclear magnetic resonance (qNMR) has been gaining attention as a purity assessment method. In particular, qNMR is recognized as the primary method to realize the Internal System of Units (SI) in organic analysis. The capability of quantitative analysis is recognized as the beginning of NMR development. NMR signals are proportional to the number of nuclei and qNMR has been used in various fields, such as metabolomics and food and pharmaceutical analysis. However, careful sample preparation and thorough optimization of measurement parameters are required to obtain accurate and reliable results. In this review, quantitative methods used in qNMR are discussed, and the important factors to be considered also introduced. The recent development of qNMR techniques including combination with chromatography and, multidimensional NMR are also presented.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.517-526
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• 1999

This paper deals with two economic optimal designs of constant-stress accelerated life test(ALT) where failure distribution follows one of location-scale family, i. e., exponential, Weibull, and lognormal distributions which have been ones of the popular choices of failure distributions. Two optimization criteria to develop ALT plans are the statistical efficiency per unit expected cost which consists of the fixed test cost, cost being proportional to the number of test units, and variable test cost depending on test period and stress level, and the expected loss which combines Taguchi's quadratic loss function and expected test cost. Optimum plan determines the low stress level, test units allocated to each stress, and censoring times at two stress levels under Type I censoring. The proposed ALT plans are illustrated with a numerical example and sensitivity analyses are conducted to study effects of pre-estimates of design parameters.