• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.144-149
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• 2006

This paper deals with a balanced model reduction for uncertain nonlinear systems via T-S fuzzy approach. We define a generalized controllability/observability gramian and obtain a balanced state space model using generalized gramians which can be obtained from solutions of linear matrix inequalities. We present a balanced model reduction scheme by truncating not only state variables but also uncertain elements. An upper bound of the model reduction error will also be suggested. In order to demonstrate the efficacy of our method, a numerical example will be presented.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.6
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• pp.55-64
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• 2001

Industrial machines are sometimes exposed to the danger of earthquake. In the design of a mechanical system, this factor should be accounted for from the viewpoint of reliability to analyze a complex nonlinear structure system under random excitation is proposed. First, the actual random excitation, such as earthquake, is approximated to the corresponding Gaussian process for the statistical analysis. The modal equations of overall system are expanded sequentially. Then, the perturbed equations are synthesized into the overall system and solved in probabilistic way. Several statistical properties of a random process that are of interest in random vibration are evaluated in each substructure. Comparing with the results of the numerical simulation proved the efficiency of the proposed method.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.4
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• pp.54-64
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• 2005

The study investigated genetic algorithms for the optimal control model of maximum height vertical jumping. The model includes forward dynamic simulations by the neural excitation-control variables. Convergence of genetic algorithms is very slow. In this paper the micro genetic algorithm(micro-GA) was used to reduce the computation time. Then a near optimal solution from micro-GA was an initial solution for VF02, which is one of well-developed and proven nonlinear programming algorithms. This approach provided the successful optimal solution for maximum-height jumping without a reasonable initial guess.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.87-92
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• 2007

Recently, developments of process monitoring system in order to detect and diagnose process abnormalities has got the spotlight in process systems engineering. Normal data obtained from processes provide available information of process characteristics to be used for modeling, monitoring, and control. Since modern chemical and environmental processes have high dimensionality, strong correlation, severe dynamics and nonlinearity, it is not easy to analyze a process through model-based approach. To overcome limitations of model-based approach, lots of system engineers and academic researchers have focused on statistical approach combined with multivariable analysis such as principal component analysis (PCA), partial least squares (PLS), and so on. Several multivariate analysis methods have been modified to apply it to a chemical process with specific characteristics such as dynamics, nonlinearity, and so on.This paper discusses about missing value estimation and sensor fault identification based on process variable reconstruction using dynamic PCA and canonical variate analysis.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.55-57
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• 2000

대규모의 전력을 사용하며 전력 수요가 일정하지 않고 변동하는 제철소의 전기아크로 (electric arc furnace) 부하는 전압 플릭커 (voltage flicker) 등 전력품질을 저하시키는 현상의 주 원인이 되고 있다. 따라서, 전력품질의 향상을 위한 전력계통의 계획과 운용에 있어서 이러한 부하들의 비선형적인 전압-전류 특성을 해석하고 모델링하는 것이 우선 되어야 한다. 특히 전기아크로 부하의 비선형적이고 랜덤 신호에 가까운 특성은 stochastic 접근법에 의해 주로 모델링되어 왔으나, 전기아크로 부하에 의한 전력계통에서의 영향을 평가를 위해서는 deterministic 접근법에 의한 모델링이 필요하며 전기아크로 부하가 가지는 chaos 특성을 Lorenz 시스템으로 표현한 부하모델이 개발되었다[1]. 개발된 모델에 의해 하나의 chaos 시스템으로 예측된 전기아크로 부하 패턴은 전 동작 범위에서 부하 특성을 정확하게 반영하는데 문제가 있다. 따라서, 전기아크로 부하 패턴을 표현할 수 있는 복수의 chaos 시스템을 이용하여 보다 나은 예측 특성을 가진 부하 모델의 개발이 필요하다. 본 논문에서는 기존의 Lorenz 시스템과 전기아크로 부하의 고주파영역 특성을 보다 적절하게 반영할 수 있는 Logistic 시스템을 혼합한 형태의 chaos 모델을 개발하고, 전력 계통에서의 전력품질 저하현상을 정량화하는 지수를 통해 모델의 유용성과 정확성을 검증하고자 한다.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.57-65
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• 2015

Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.349-354
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• 2015

This paper presents the stability conditions of the Takagi-Sugeno (T-S) fuzzy sampled-data filter. The error system between the T-S fuzzy system and fuzzy filter is presented. In the sense of the Lyapunov stability analysis, the stability conditions are given, which can be represented in terms of linear matrix inequalities (LMIs). The proposed stability conditions utilize the different approach from the conventional methods, and have better performance than that of the conventional ones. The simulation example is given to show the effectiveness of the proposed method.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.147-150
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• 2012

While LDA is a supervised dimension reduction method which finds projective directions to maximize separability between classes, the performance of LDA is severely degraded when the number of labeled data is small. Recently semi-supervised dimension reduction methods have been proposed which utilize abundant unlabeled data and overcome the shortage of labeled data. However, matrix computation usually used in statistical dimension reduction methods becomes hindrance to make the utilization of a large number of unlabeled data difficult, and moreover too much information from unlabeled data may not so helpful compared to the increase of its processing time. In order to solve these problems, we propose an ensemble approach for semi-supervised dimension reduction. Extensive experimental results in text classification demonstrates the effectiveness of the proposed method.

• Journal of the Korean GEO-environmental Society
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• v.23 no.2
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• pp.13-23
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• 2022

The ground-structure interaction of the bridge foundation has been pointed out as a major factor influencing the behavior of the bridge during earthquakes. In this study, the effect of characteristics of ground and bridge foundation on the earthquake vulnerability is investigated. From the pseudo-static analysis, it is confirmed that non-linearity becomes lesser and horizontal load becomes greater when surcharge is considered. It is also found that as the ground worsens and the size of foundation decreases, horizontal load reduces. To derive reasonable structural model for bridge foundation, fragility curve is obtained considering four conditions (fixed condition, equivalent linear condition, non-linear without surchage condition, non-linear with surcharge condition) and compared. Seismic analysis is performed on single pier with Opensees. From the earthquake vulnerability analysis, it is found that shallow foundation can be assumed as fixed condition. In conservative approach, stiffness of spring can be obtained based on Korean highway bridge design code for pile foundation which can consider the ground condition.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.132-139
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• 2019

Bi-directional interaction between vegetation and groundwater table has a great influence on the dynamics of wetland vegetation. In this study, nonlinear dynamics of wetland vegetation affected by groundwater are analyzed. The effect on groundwater is described as a loss term in the governing equation of wetland vegetation and it is explored how the wetland vegetation is likely to converge into two attractors by groundwater table change. From this conceptual approach, the vulnerability to catastrophic shifts in stable state where the current vegetation species are extinct and stabilized by other vegetation species is analyzed in response to groundwater table.