• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.161-174
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• 2000

Bayesian inversion is a stable approach to infer the subsurface structure with the limited data from geophysical explorations. In geophysical inverse process, due to the finite and discrete characteristics of field data and modeling process, some uncertainties are inherent and therefore probabilistic approach to the geophysical inversion is required. Bayesian framework provides theoretical base for the confidency and uncertainty analysis for the inference. However, most of the Bayesian inversion require the integration process of high dimension, so massive calculations like a Monte Carlo integration is demanded to solve it. This method, though, seemed suitable to apply to the geophysical problems which have the characteristics of highly non-linearity, we are faced to meet the promptness and convenience in field process. In this study, by the Gaussian approximation for the observed data and a priori information, fast Bayesian inversion scheme is developed and applied to the model problem with electric well logging and dipole-dipole resistivity data. Each covariance matrices are induced by geostatistical method and optimization technique resulted in maximum a posteriori information. Especially a priori information is evaluated by the cross-validation technique. And the uncertainty analysis was performed to interpret the resistivity structure by simulation of a posteriori covariance matrix.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1135-1148
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• 2018

Previous studies on reservoir operation have been assumed that the climate in the future would be similar to that in the past. However, in the presence of climate non-stationarity, Robust Optimization (RO) which finds the feasible solutions under broader uncertainty is necessary. RO improves the existing optimization method by adding a robust term to the objective function that controls the uncertainty inherent due to input data instability. This study proposed Robust-SDP that combines Stochastic Dynamic Programming (SDP) and RO to estimate dam operation rules while coping with climate non-stationarity. The future inflow series that reflect climate non-stationarity were synthetically generated. We then evaluated the capacity of the dam operation rules obtained from the past inflow series based on six evaluation indicators and two decision support schemes. Although Robust-SDP was successful in reducing the incidence of extreme water scarcity events under climate non-stationarity, there was a trade-off between the number of extreme water scarcity events and the water scarcity ratio. Thus, it is proposed that decision-makers choose their optimal rules in reference to the evaluation results and decision support illustrations.

• Knowledge Management Research
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• v.22 no.4
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• pp.119-133
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• 2021

As a large amount of data is produced in each industry, a number of time series pattern prediction studies are being conducted to make quick business decisions. However, there is a limit to predicting specific patterns in nonlinear time series data due to the uncertainty inherent in the data, and there are difficulties in making strategic decisions in corporate management. In addition, in recent decades, various studies have been conducted on data such as demand/supply and financial markets that are suitable for industrial purposes to predict time series data of irregular random walk models, but predict specific rules and achieve sustainable corporate objectives There are difficulties. In this study, the prediction results were compared and analyzed using the Chaos analysis method for roulette data and financial market data, and meaningful results were derived. And, this study confirmed that chaos analysis is useful for finding a new method in analyzing time series data. By comparing and analyzing the characteristics of roulette games with the time series of Korean stock index future, it was derived that predictive power can be improved if the trend is confirmed, and it is meaningful in determining whether nonlinear time series data with high uncertainty have a specific pattern.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.2
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• pp.33-44
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• 2008

Most of the civil structure - bridges, offshore structures, plant, etc. - have been designed by the classical approaches which deal with all the design parameters as deterministic variables. However, some more advanced techniques are required to evaluate the inherent randomness and uncertainty of each design variable. In this research, a seismic safety assessment algorithm based on the structural reliability analysis has been formulated and computerized for more reasonable seismic design of turbine-generator foundations. The formulation takes the design parameters of the system and loading properties as random variables. Using the proposed method, various kinds of parametric studies have been performed and probabilistic characteristics of the resulted structural responses have been evaluated. Afterwards, the probabilistic safety of the system has been quantitatively evaluated and finally presented as the reliability indexes and failure probabilities. The proposed procedure is expected to be used as a fundamental tool to improve the existing design techniques of turbine-generator foundations.

• Smart Structures and Systems
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• v.25 no.2
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• pp.155-167
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• 2020

This paper demonstrates a real-time hybrid substructuring (RTHS) shake table test to evaluate the seismic performance of a base isolated building. Since RTHS involves a feedback loop in the test implementation, the frequency dependent magnitude and inherent time delay of the actuator dynamics can introduce inaccuracy and instability. The paper presents a robust stability and performance analysis method for the RTHS test. The robust stability method involves casting the actuator dynamics as a multiplicative uncertainty and applying the small gain theorem to derive the sufficient conditions for robust stability and performance. The attractive feature of this robust stability and performance analysis method is that it accommodates linearized modeled or measured frequency response functions for both the physical substructure and actuator dynamics. Significant experimental research has been conducted on base isolators and dampers toward developing high fidelity numerical models. Shake table testing, where the building superstructure is tested while the isolation layer is numerically modeled, can allow for a range of isolation strategies to be examined for a single shake table experiment. Further, recent concerns in base isolation for long period, long duration earthquakes necessitate adding damping at the isolation layer, which can allow higher frequency energy to be transmitted into the superstructure and can result in damage to structural and nonstructural components that can be difficult to numerically model and accurately predict. As such, physical testing of the superstructure while numerically modeling the isolation layer may be desired. The RTHS approach has been previously proposed for base isolated buildings, however, to date it has not been conducted on a base isolated structure isolated at the ground level and where the isolation layer itself is numerically simulated. This configuration provides multiple challenges in the RTHS stability associated with higher physical substructure frequencies and a low numerical to physical mass ratio. This paper demonstrates a base isolated RTHS test and the robust stability and performance analysis necessary to ensure the stability and accuracy. The tests consist of a scaled idealized 4-story superstructure building model placed directly onto a shake table and the isolation layer simulated in MATLAB/Simulink using a dSpace real-time controller.

• Journal of the Korean Geotechnical Society
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• v.18 no.4
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• pp.119-126
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• 2002

A reliability analysis is performed to investigate the influence of the uncertainty from few in-situ samples and inherent heterogeneity of the ground on the probability of failure for a rock cut slope. The results are compared with those of deterministic slope stability analysis. The random variables used are unit weight of the rock, the angle of potential slope of failure, and cohesion and internal friction angle of joints. It was found that the rock slope in which the factor of safety satisfied the minimum safety factor in the deterministic analysis has high probability of failure in the reliability analysis when the weak geological strata are involved in the cut slope. The probability of failure of rock slope is most sensitive to the mean and standard deviation of cohesion in rock joint among the random soil parameters included in the reliability analysis. Sensitivities of the mean values are larger than those of standard deviations, which means that accurate estimation of the mean for the in-situ geotechnical properties is important.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.477-486
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• 2001

In this paper , we study the problem of designing TS(Takagi-Sugeno) fuzzy controllers for the systems that can be approximated or represented by the TS fuzzy model. The main strategy used in this paper is the inverse optimal approach, in which the cost function is determined later than the Lyapunov function and its corresponding control input satisfying the design requirements such as stability, decay rate, and robustness against uncertainty. This approach is useful because it yields controllers satisfying the inherent robustness of optimal controllers as well as the considered design goals. The design procedures established in this paper are all in the from of solving LMIs(Iinear matrix inequalities). Since the LMIs arising in the design procedures can be solved within a given tolerance by the interior point methods. the design method of the paper are efficient in practice. The applicability of the proposed design procedures is demonstrated by design examples.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.145-153
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• 2014

Several studies regarding drought indices and criteria have been widely studied in the literature. If one defines the onset, severity, and end of droughts, in general, a certain threshold needs to be set to assess the drought events. However, the uncertainty associated with the threshold is a critical problem in drought analysis. To take full advantage of the inherent features in the rainfall series, a Hidden Markov Model (HMM) based probabilistic drought analysis was proposed rather than using the existing threshold based analysis. As a result, the proposed HMM based probabilistic drought analysis scheme shows better performance in terms of defining drought state and understanding underlying characteristics of the drought. In addition, the HMM based approach is capable of quantifying the uncertainties associated with the classifying meteorological drought condition in a systematic way.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.436-443
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• 2014

This study was begun on the premise that architecture which has the definite disposition for survival even in the urban, social structure of that uncertainty and constructs specialty is biomorphic architecture. This study was organic philosophy background analysis of Biomorphic architecture occurrence, through meaning inherent analysis in Biomorphic architecture, which going to be deployed atypical and new shape one. Biomorphic architecture is organism shape of structure of autonomous survival, which is shaped the potential of biological phenomena. Theoretical analysis of the Biomorhpic architecture characteristic was analysed. Factor in the occurrence of Biomorphic architecture based on an objective analysis of the research is characteristic analysis. Which is reason as the 'create', the science of complexity and emergent System. The generation causes of biomorphic architecture are an organic philosophy. Biomorphic architecture makes the realization of simile form using the procedural principle represented by in natural phenomena.

• Journal of Korean Society of Steel Construction
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• v.18 no.4
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• pp.481-490
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• 2006

The actual performance of a building during an earthquake depends on many factors. The prediction of the seismic performance of a new or existing structure is complex, due not only to the large number of factors that need to be considered and the complexity of the seismic response, but also due to the large inherent uncertainties and randomness associated with making these predictions. A central issue of this research is the proper treatment and incorporation of these uncertainties and randomness in the evaluation of structural capacity and response has been adopted in the seismic performance evaluation of steel tall buildings to account for the uncertainties and randomness in seismic demand and capacities in a consistent manner. The basic framework for reliability-based seismic performance evaluation and the key factors for statistical studies were summarized. A total of 36 target structures that represent typical tall steel buildings based on national building code (KBC-2005) were designed for the statistical studies of demand factor s and capacity factors. The incremental dynamic analysis (IDA) approach was examined through the simple steel moment frame building in determination of global drift capacity.