• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data (a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology fur sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• Journal of applied mathematics & informatics
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• v.41 no.1
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• pp.107-121
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• 2023

An epidemic infectious disease model consists of six compartments viz. Susceptible, Exposed, Infected, Quarantine, Recovered, and Virus with nonlinear saturation incidence rate is proposed to know the viral disease dynamics. There exist two biological equilibrium points for the model system. The system's local and global stability is done through Lyapunov's direct method about equilibrium points. The sensitivity analysis has been performed for the basic reproduction number and equilibrium points through the normalized forward sensitivity index. Sensitivity analysis shows that virus growth and quarantine rates are more sensitive parameters. In support of mathematical conclusions, numerical experimentation has been shown.

• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.152-158
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• 2005

This paper describes a reactive optimal power flow incorporating margin enhancement constraints. Margin sensitivity at a steady-state voltage instability point is calculated using invariant space parametric sensitivity, and it can provide valuable information for selection of effective control parameters. However, the weakest buses in neighboring regions have high margin sensitivities within a certain range. Hence, the control determination using only the sensitivity information might cause violation of operational limits of the base operating point, at which the control is applied to enhance voltage stability margin in the direction of parameter increase. This paper applies an interior point method (IPM) to solve the optimal power flow formulation with the margin enhancement constraints, and shunt capacitances are mainly considered as control variables. In addition, nonlinearity of margin enhancement with respect to control of shunt capacitance is considered for speed-up control determination in the numerical example using the IEEE 118-bus test system.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.187-194
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• 2014

We consider a Bayesian nonignorable selection model to accommodate the selection bias. Markov chain Monte Carlo methods is known to be very useful to fit the nonignorable selection model. However, sensitivity to prior assumptions on parameters for selection mechanism is a potential problem. To quantify the sensitivity to prior assumption, the deviance information criterion and the conditional predictive ordinate are used to compare the goodness-of-fit under two different prior specifications. It turns out that the 'MLE' prior gives better fit than the 'uniform' prior in viewpoints of goodness-of-fit measures.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.1-8
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• 2007

In recent, the issues of sensitivity and psychology of human have received much attention from researchers and practitioners. In this paper. we analyze the information of color and location in order to detect the sensitivity and psychology by means of human vision on color space organization in a presented picture. After this process, we propose a method to determine psychology states through the space organization by using a fuzzy membership function which can be used to analyze direction information for the sensitivity. The proposed method is applied to the psychology states based on the space organization of Alschuler and Hattcick's method and to the space organization of Gunnwald's method. As a result, we present that the proposed method is very similar to a pattern classification of Alschuler and Grunwald.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.644-645
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• 2007

In this paper, the eigenvalue sensitivity analysis algorithm in discrete systems by the RCF method are presented and applied to the power system including TCSC. The RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of dominant oscillation modes after periodic switching operations. These simulation results are very different from those of the conventional continuous system analysis method such as the state space equation method

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.623-630
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• 2003

Recently, Tanaka(1988) derived two influence functions related to an eigenvalue problem $(A-\lambda_sI)\upsilon_s=0$ of real symmetric matrix A and used them for sensitivity analysis in principal component analysis. In this paper, we deal with the perturbation expansions up to quadratic terms of the same functions and discuss the application to sensitivity analysis in principal component regression analysis(PCRA). Numerical example is given to show how the approximation improves with the quadratic term.

• Journal of the Korean Data and Information Science Society
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• v.2
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• pp.1-9
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• 1991

Shin, Tarumi and Tanaka(1989) discussed a method of sensitivity analysis in principal component regression(PCR) based on an influence function derived by Tanaka(1988). The present paper is its continuation. In this paper we first consider two new influence measures, then apply the proposed method to various data sets and discuss some properties of sensitivity analysis in PCR.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.508-512
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• 1997

Design sensitivity analysis of Eigen Problem give systematic design improvement information for noise and vibration of a system. Based on reliable results form commercial FE code(UAI/NASTRAN), three computational procedures for design sensitivity analysis of eigen problem are suggested. Those methods are finite difference,design sensitivity analysis using external module and design sensitivity analysis running with NASTRAN. To verify the suggested methods, a numerical example is given and these results are compared with the results from UAI/NASTRAN eigen sensitivity option. We can conclude that design sensitivity coefficient of eigen proplems can be computed outside of the FE code as easy as inside of the FE code.

• Journal of the Korean Home Economics Association
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• v.41 no.9
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• pp.69-83
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• 2003

Today, because of the consumers who should constantly decide which to buy in a flood of information can't search for complete information by the limited time and the lack of the ability in evaluating the goods, the price being important as the information clue in consumers' goods or dependence on the price will be gradually increasing. The purpose of this study is to know how much price sensitivity recognized by consumers will have and effect on buying feeling of satisfaction in internet shopping mall. The result of this study is that the consumers' target-oriented behavior searching appropriate price for buying goods in internet shopping mall substantially elevates the price sensitivity and shapes the positive attitude toward the feeling of satisfaction. It is meaningful in that it has provided the base for studying the price sensitivity centering around some limited factors through actual proof of how the consumers respond to the price at this point of activating online transactions.