• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.8
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• pp.469-476
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• 2004

In this paper, a 3D shape optimization algorithm which guarantees a smooth optimal shape is presented using parameterized sensitivity analysis. The design surface is parameterized using Bezier spline and B-spline, and the control points of the spline are taken as the design variables. The parameterized sensitivity for the control points are found from that for nodal points. The design sensitivity and adjoint variable formulae are also derived for the 3D non-linear problems. Through an application to the shape optimization of 3D electromagnet to get a uniform magnetic field, the effectiveness of the proposed algorithm is shown.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3B
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• pp.138-143
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• 2005

This paper aims to optimize an access probe algorithm for the CDMA 2000 system. The incremental value of PWR_STEP increases as NUM_STEP as 1dBm±0.2 for access probe of the area with good receiving sensitivity when the mobile station transmits via access channel and does not receive any ACK message. However, for the area with weak receiving sensitivity, according to the algorithm of open-loop power control, the transmitting power amplifier becomes saturated and PWR_STEP incremental value keeps performing access probe to 0dBm±0.2. Therefore interference and battery consumption increases according to the transmission of the mobile station. We have optimized the access probe algorithm according to the receiving sensitivity. We transmit the incremental value of access probe power, with delaying as much RT slot value as indicated by IS-95C standard in case of good receiving sensitivity and with delaying RT+l slot value in case of weak receiving sensitivity. Simulation results showed that the proposed algorithm contributes to decrease of the interference and battery consumption according to the transmitting power of the mobile station and improves the call duration.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.8
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• pp.96-103
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• 2008

In this paper, a new algorithm based on sensitivity method for alleviating overloads in power networks is presented to find the switching branches effectively. By applying the new sensitivity of the line flow with respect to the change of the branch impedance, both on and off switchings for alleviating overloads in power networks are performed systematically at once and an effective scheme for drawing up a plan to alleviate overloads of the lines is presented through screening a large number of line switching cases easily. The ranking of switching branches is calculated according to the new switching algorithm based on sensitivity method and the switching of the ranked branches is performed in the order of ranking until overloads are eliminated. In order to show the effects of this algorithm, it is applied to a small scale power system of IEEE 39-bus test system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.04a
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• pp.38-45
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• 1994

The general conceptual constitution of structural optimization is formulated. The algorithm using the gradient projection method and design sensitivity analysis is discussed. Examples of minimum-weight design for six-story steel plane frame are taken to illustrate the application of this algorithm. The advantages of this algorithm such as marginal cost and design sensitivity analysis as well as system analysis are explained.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.93-96
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• 1991

This paper describes a new algorithm based on design sensitivity analysis for optimal shape design of electrostatic devices. The design sensitivity, the variation of the object function with respect to the design variables, is derived by using implicit differentiation and direct boundary element methods. The proposed algorithm is applied to the optimal shape design of a concentric cable and the rod electrode enclosed by earthed case, It is shown, from the numerical results, that the algorithm is very usefull for the optimal shape design of the electrostatic devices.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.735-741
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• 2009

This paper presents an algorithm for the permanent magnet shape optimization of a large scale BLDC(Brushless DC) motor to minimize the cogging torque. A response surface method (RSM) using multiquadric radial basis function is employed to interpolate the objective function in design parameter space. In order to get a reasonable response surface with relatively small number of sampling data points, additional sampling points are added on the basis of design sensitivity analysis computed by using FEM. The algorithm has 2 stages: the first stage is to determine the PM arc angle, and the 2nd stage is to optimize the magnet pole shape. The developed algorithm is applied to a 5MW BLDC motor to get a minimum cogging torque. After 3 iterations with 4 design parameters, the cogging torque is reduced to 13.2% of the initial one.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.355-360
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• 2012

It is difficult to converge power flow for the power system planning data. The main cause of power flow diverse is reactive power imbalance. A active power could be adjust by ELD or merit order but a reactive power couldn't dispatch before power flow analysis. The lack of reactive power of power system is cause a inadequate voltage drop This paper suggest new reactive power dispatch algorithm using switched shunt admittance. This algorithm uses reactive power sensitivity called switch shunt jacobian. When proposed algorithm applies to real system data that couldn't be conversed in PSS/E the power flow analysis is converged.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.531-535
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• 2004

A new method is presented to construct a classifier. This was accomplished by combining a generalized regression neural network (GRNN) and a genetic algorithm (GA). The classifier constructed in this way is referred to as a GA-GRNN. The GA played a role of controlling training factors simultaneously. The GA-GRNN was applied to classify 4 different Promoter sequences. The training and test data were composed of 115 and 58 sequence patterns, respectively. The classifier performance was investigated in terms of the classification sensitivity and prediction accuracy. Compared to conventional GRNN, GA-GRNN significantly improved the total classification sensitivity as well as the total prediction accuracy. As a result, the proposed GA-GRNN demonstrated improved classification sensitivity and prediction accuracy over the convention GRNN.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.6
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• pp.259-266
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• 2005

Short-term load forecasting algorithm using neural networks and the sensitivity of temperatures in the summer season is proposed. In recent 10 years, many researchers have focused on artificial neural network approach for the load forecasting. In order to improve the accuracy of the load forecasting, input parameters of neural networks are investigated for three training cases of previous 7-days, 14-days, and 30-days. As the result of the investigation, the training case of previous 7-days is selected in the proposed algorithm. Test results show that the proposed algorithm improves the accuracy of the load forecasting.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.3
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• pp.16-24
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• 1992

In this paper, we solve the problem of designing a robust optimal controller which minimizes the H$\infty$-norm of the mixed sensitivity function matrix for linear multivariable systems. For a given minimized value, ${\gamma}$>o, an algorithm of finding all stabilizing controllers, such that the H$\infty$-norm of the mixed sensitivity function matrix is less than ${\gamma}$, is developed. The proposed algorithm, which is based on the model-matching and the interpolation theory, can be used for the H$\infty$-optimization problem.