• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.232-234
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• 1998

In this paper, we are considered various possible disturbance conditions in order to design controller, $H_{\infty}$ optimal controller is successfully designed to control in such as situations. To do this, we are determined weighting function and design parameter $\gamma$ to method of trial and error by Glover-Doyle algorithm. To compare with $H_{\infty}$-PSS and conventional-PSS which is applied in nominal system and load variations, the dynamic characteristics of $H_{\infty}$-PSS controller was verified which has a good response.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.37.4-37
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• 2001

This paper presents a vibration-rejection control design for a magnetic suspension system which has strong non-linearity, open-loop unstable characteristics, high-order flexible modes, and parameter variations. The target plant to be controlled consists of a U-core electromagnet and a flexible rail. We describe the test rig and formulate the mathematical model and then we set up a control problem as the mixed sensitivity problem where the augmented plant is constructed with frequency weighting functions and the feedback controller is designed by using the H$\infty$ controller. The effectiveness of the designed controller for the magnetic suspension system with high-order flexible modes is validated and justified using several simulations. These results show that the magnetic suspension system is robustly stable against disturbance and gives the well-damped tracking performance ...

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.285-288
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• 2006

Most previous studies on improving the effectiveness of CBR have focused on the similarity function aspect or optimization of case features and their weights. However, according to some of the prior research, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. Nonetheless, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors that combine, as well as the weight of each feature. The new model is applied to the real-world case of a major telecommunication company in Korea in order to build the prediction model for the customer profitability level. Experimental results show that our GA-optimized CBR approach outperforms other AI techniques for this mulriclass classification problem.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.429-430
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• 2019

본 논문에서는 최적화 기법에 기반한 지능형 시스템의 재무응용사례를 다룬다. 본 연구에서 제안하는 모형은 대표적인 최적화 기법 중 하나인 시뮬레이티드 어니일링인데 이는 유전자 알고리듬과 유사한 최적화 성능을 가지고 있는 것으로 알려져 있으나 재무분야에서 응용된 사례가 거의 없다. 본 연구에서 제안하는 지능형 시스템은 시뮬레이티드 어니일링과 기계학습 기법을 결합한 것이다. 일반적으로 최적화와 기계학습 기법을 결합하는 방법은 특징선택(feature selection), 특징 가중치 최적화(feature weighting), 사례선택(instance selection), 모수 최적화(parameter optimization) 등의 방법이 있는데 선행연구에서 가장 많이 사용된 것은 특징선택에 두 기법을 결합하는 방식이다. 본 연구에서도 기계학습 기법을 재무 문제에 활용함에 있어서 최적의 특징선택을 위해 시뮬레이티드 어니일링을 결합하는 방식을 사용한다. 본 연구에서 제안된 기법의 유용성을 확인하기 위하여 실제 재무분야의 데이터를 활용하여 예측 정확도를 확인하였으며 그 결과를 통하여 제안하는 모형의 유용성을 확인할 수 있었다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.339-349
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• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.3
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• pp.299-306
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• 2002

The load frequency control(LFC) of power system is one of important subjects in view of system operation and control. That is, even though the rapid load disturbances are applied to the given power system, the stable and reliable power should be supplied to the users, converging unconditionally and rapidly the frequency deviations and the tie-line power flow ones of each area into allowable boundary limits. Nonetheless of such needs, if the internal parameter perturbation and the sudden load variation are given, the unstable phenomena of power systems can be often brought out because of the large frequency deviation and the unsuppressible power line one. So, an optimal modulation controller for UC of multi-area power system is designed by a recursive algorithm that determines the state weighting matrix Q of a linear quadratic performance criterion. The optimal modulation controller is based on optimal control and can obtain the exact dynamic response of the UC of multi-area power system in the time domain. The performances of the resultant optimal modulation control, that is, the steady-state deviations of frequency and tie-line power flow and the related dynamics, were investigated and analyzed in detail by being applied to the UC of multi-area power system in the perturbations of predetermined internal parameters. Through the simulation results tried variously in this paper for disturbance of stepwise load changes, the superiorities of the proposed optimal modulation controller in robustness and stability were proved.

• Journal of Broadcast Engineering
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• v.8 no.3
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• pp.268-277
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• 2003

In this paper, we propose a new video watermarking method exploiting the human visual system (HVS) to find effective locations. in the video frames which make the watermark robust and imperceptible simultaneously. In particular, we propose a new HVS-optimized weighting map for hiding the watermark by considering HVS in three different aspects : frequency, spatial, and motion masking effects. The global masking map is modeled by combining the frequency masking, the spatial masking, and the motion masking. In this paper, we use a watermark which is generated by the bitwise exclusive-OR operation between a logo image and a random sequence. The amount of watermarks is weighted by a control parameter. Furthermore, we embed the watermark in the uncompressed video sequence for the general watermarking method available to various coding schemes. Simulation results show that the watermark is imperceptible and the proposed method is good for watermark capacity. It is also demonstrated that the proposed method is robust against various attacks, such as MPEG coding, MPEG re-encoding, and frame attacks.

• Geotechnical Engineering
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• v.3 no.1
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• pp.65-76
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• 1987

This study has been carried out as a basic course for the analysis of foundation deformations based on the Cap model using the finite element methods. Material parameters should firstly be determined in order to use the Cap model for numerical solution. Associated with the fact described above, a method determining the soil parameters is suggested using algorithm for numerical ana])isis from raw truly triaxial compression laboratory test data of Pueblo.Colorado sand by Zaman, et at. (1982) More specifically, the change of soil parameters Is thoroughly examined by weighting the data obtained from CTC and RTE tests, respectively. The main results obtained are as follows; 1. The obtained values of parameters (E, V and 2) are same irrespective of data obtained from various kind of tests. 2. The values of the other parameters are dependent on data used. 3. The determination of parameters is little affected by the weighting factor.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.221-227
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• 2014

In this paper, we propose a synthesis method that can effectively suppress the ambience which affects tonal components in the PS decoder. Ambience component was obtained by using decorrelation filter and the weighting of the ambience in the decoder was determined through IC parameter. However, since the parameters are extracted in the sub-band domain, a low IC value could be analyzed even if the tonal component is dominant. The quality of the output signal may be degraded. To prevent this problem, the tonality was measured in the downmixed signal and the weighting of the ambience components were adjusted appropriately according to the measured tonality index. The performance of the proposed method was evaluated by simulations. Furthermore, the subjective test was performed and the results confirmed that the proposed method offers improved quality.

• Atmosphere
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• v.24 no.1
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• pp.101-110
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• 2014

This study estimates and evaluates the daily January temperature from 2003 to 2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regression on Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjusted to 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in terms of bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then compared with that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimating the temperature over Jeju island, K-PRISM has the lowest bias (-0.85) and RMSE (1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation of observation, but tends to underestimate due to a high-discrepancy in mean altitudes between the observation stations and grid points of the 30 m topography. The temperature over South Korea derived from K-PRISM represents a detailed spatial pattern of the observed temperature, but generally tends to underestimate with a mean bias of -0.45. In bias terms, the estimation ability of K-PRISM differs between grid points, implying that care should be taken when dealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate 30 m-resolution temperature over South Korea, and reflect topographically diverse signals with detailed structure features.