• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.499-505
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• 2006

Regularlization approach to regression can be easily found in Statistics and Information Science literature. The technique of regularlization was introduced as a way of controlling the smoothness properties of regression function. In this paper, we have presented a new method to evaluate linear and non-linear fuzzy regression model based on Tanaka's model using the idea of regularlization technique. Especially this method is a very attractive approach to model non -linear fuzzy data.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.313-319
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• 1997

There is currently a focus on usability of interactive computer software. Previous research in software ergonomics has indicated the importance of evaluating the usability of software user interfaces. Software developers, interface designers or human foctors engineers often confront the task of comparative evaluation among systems, versions or interface designs. This study presents a structured model for comparative evaluation of user interface designs using usability criteria and measures. The proposed model consists of twomain phases : the prescreening phase ad the evaluation phase. The first phase involves expert judgment-based approach with qualitative criteria. The prescreening phase uses absolute measurement analytic hierarchy process to filter possible altermative interfaces to a reasonable subset. The second phase involves user-based approach such as usability testing, with quantitative criteria. The objective of the evaluation phase is to evaluate a subset of altermatives using objective measures. A set of criteria and measures for evaluating the usability of computer software designs is presented. The proposed model provides practitioners with a structured approach to select the best interface based on usability criteria and measures.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.373-376
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• 2006

In general, there are three kinds of methods in analyzing dynamic robust design experiment: loss model approach, response function approach, and response model approach. In this talk, we review the three modeling approaches in terms of several criteria in comparison. This talk also generalizes the response model approach based on a generalized linear model. We develop a generalized two-step optimization procedure to substantially reduce the process variance by dampening the effect of both explicit and hidden noise variables. The proposed method provides more reliable results through iterative modeling of the residuals from the fitted response model. The method is compared with three existing approaches in practical examples.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.258-260
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• 2007

MAS based market simulator has attracted the attentions of people who are interested in using or developing electricity market simulator. MAS based approach makes it possible to model each market participant's strategic behaviors. Traditional market simulators have used optimization formulation to model market operation, which has been used since vertically integrated system. Optimization mainly uses cost minimization or welfare maximization of entire system. Therefore it is somehow difficult to model the independently strategic behaviors of market participants. MAS is one of AI technology based on distributed intelligence which makes it possible to model independently acting entities in competitive market. This paper proposes the method to model strategic participants in electricity market based on MAS.

• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Journal of Korean Society of Transportation
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• v.9 no.2
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• pp.27-40
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• 1991

Delay is an widely-used tool for evaluating the operation of signalized intersections. This paper presents two mathematical models: a model converting stop delay into approach delay : and a model estimating delay at isolated signalized intersection. To develop the delay-conversion model, actual stop delay and approach delay experienced by individual vehicles were measured and then their relationship was formulated using ma-thematical procedure. the formula expressing the approach-delay to stop-delay ratio was a monotonously decreasing function of effective red time. New delay model was developed based on the following criteria; the fitness to measured delay for undersaturated traffic condition and the convergence to the deterministic overflow delay for oversaturated traffic condition. Performance of this model was better than those of other existing models based on the comparison study.

• Survey Research
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• v.2 no.1
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• pp.73-86
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• 2001

In this paper. we conducted an empirical study to investigate the design and weighting effects on descriptive and analytic statistics. We compared the regression models using the design-based approach and the generalized estimating equations (GEEs) approach with the model-based approach through the design and weighting effects analysis.

• 한국디지털정책학회:학술대회논문집
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• 2006.06a
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• pp.197-204
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• 2006

This paper tried to develop differentiation strategies of policy process in governance. Firstly, we reviewed model of policy making(output-oriented model and process-oriented model, normative or idealistic approach and realistic or empirical approach, rational model and cognitive model etc). Now gumi city is making the policy based on the process-oriented model, realistic or empirical approach, cognitive model. So gumi city was winner the test of provinces innovation in 2005. Therefore, when we make the policy, consider these factor: citizen and public service personnel participate policy making process and control policy quality.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.06a
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• pp.45-56
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• 2001

In this paper, we conducted an empirical study to investigate the design and weighting effects on descriptive and analytic statistics. We compared the regression models using the design-based approach and the generalized estimating equations(GEEs) approach with the model-based approach through the design and weighting effects analysis.