• Journal of the military operations research society of Korea
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• v.29 no.2
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• pp.100-110
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• 2003

Equipment replacement policy may not be defined with certainty, because physical states of any technological system may not be determined with foresight. This paper presents Markov Decision Process(MDP) model for army equipment which is subject to the uncertainty of deterioration and ultimately to failure. The components of the MDP model is defined as follows: ⅰ) state is identified as the age of the equipment, ⅱ) actions are classified as 'keep' and 'replace', ⅲ) cost is defined as the expected cost per unit time associated with 'keep' and 'replace' actions, ⅳ) transition probability is derived from Weibull distribution. Using the MDP model, we can determine the optimal replacement policy for an army equipment replacement problem.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.477-483
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• 2005

This article describes a robust state estimation method which enables to produce reliable estimates in spite of heavy perturbation including plant uncertainty and external disturbances. The main idea is to combine the standard state estimator with the perturbation observer in the estimator frame. The perturbation observer reflects equivalent quantity of plant uncertainty and external disturbances during the estimation process so that the state estimator dynamics gets as close as possible to the real plant dynamics. The robust state estimator proposed in this paper is given in a recursive discrete-time form which is very useful fur implementation purpose. In terms of the error dynamics derived for the robust state estimator, we discuss the stability issue and noise sensitivity. The effectiveness and practicality of the robust state estimator are verified through numerical examples and experimental results.

• Journal of Magnetics
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• v.19 no.1
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• pp.78-83
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• 2014

This paper proposes an efficient reliability-based optimization method for designing a superconducting magnetic energy system in presence of uncertainty. To evaluate the probability of failure of constraints, samplingbased reliability analysis method is employed, where Monte Carlo simulation is incorporated into dynamic Kriging models. Its main feature is to drastically reduce the numbers of iterative designs and computer simulations during the optimization process without sacrificing the accuracy of reliability analysis. Through comparison with existing methods, the validity of the proposed method is examined with the TEAM Workshop Problem 22.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.59-62
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• 1991

This paper describes an effective algorithm for evaluating the reliability indices and calculating the production cost for generation system with thermal, hydro and pumped storage plants. Using the Energy Invariance property, this algorithm doesn't need deconvolution process which gives large burden in computing time. In order to consider an adaptable load model, we consider the system load with forecasting uncertainty. The proposed algorithm is applied to the KEPCO system and its result shows high accuracy and less computing time.

• The Korean Journal of Financial Management
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• v.14 no.3
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• pp.319-339
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• 1997

This paper provides an empirical analysis of the winner's curse in the context of corporate takeovers. The study analyzes conditions which make overpayment likely. For a sample of corporate takeovers completed between 1982 and 1993, the analysis shows that the volatility of targets relative to that of acquirers (not the uncertainty of the target or acquirer alone) has a definitive impact on the magnitude of the winner's curse. Also, the incidence is more pronounced in multiple-bidder than in single-bidder contests. Specifically, white knights are more likely to overpay than other acquirers in multiple bidding situations. Furthermore, the study finds that the process of competitive bidding is a zero sum game since the greater returns to the shareholders of target firms in multiple-bid contests come at the expense of the acquiring companies, Overall, the evidence suggests that the bidders need to become more conservative, particularly as the relative uncertainty of the target's 'true' value and the number of bidders increase.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.1000-1011
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• 2005

This paper presents a system for medical statistical analysis that helps medical professionals analyze clinical data more easily and accurately. It is able to recommend proper methods according to the distribution of sample data, and provides guide maps composed of icons for the understanding of the process of analysis. Besides general statistical analysis, it includes commonly-used statistical methods for medical fields, such as survival analysis and methods for repetitive measurements. The results of analysis are interactively displayed by 3D glyph-based visualization with uncertainty.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.161-175
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• 2001

In this paper, a detection method of contradiction between input informations is proposed when the inference is processed in rule-based systems. The proposed method is accomplished by improving the label representation and the label management scheme in a conventional ATMS(Assumption-based Truth Maintenance System). The Proposed method also can represent and process input informations having uncertainty values.

• Korean Management Science Review
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• v.17 no.1
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• pp.31-40
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• 2000

With the rapidly changing external environment and the increasing internal process complexity more and more organizations are adopting the Electronic Approval System(EAS) for their competitiveness. This paper defines EAS as a core organizational communication medium investigates factors which influence EAS's use from a media rich-ness theory and shows sutiable EAS functions for equivocality resolution and uncertainty reduction. Results from the five EAS implementation sites show that most organizations use EAS only for tasks with low equivocality and low uncertainty. Additional functionalities such as video conferencing and database access were suggested for fu-ture EAS system to enhance their utilization for more cirtical and unstructed tasks.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.693-698
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• 1991

This paper describes a fuzzy rule-based assembly algorithm for precision parts mating, The difficulties in devising reliable assembly strategies result from the complexity of the assembly process and the uncertainty such as imperfect knowledge of the parts being assembled as well as the limitations of the devices performing the assembly. To cope with above problems, we propose an assembly algorithm utilizing fuzzy set theory. The presented method allows us to represent the uncertainty by using fuzzy membership function and treat nonlinear sapping from measured force/torque to corrective motions using rules. Finally, the performance of this method is evaluated through a series of experiments. Experimental results show that the proposed method can be effectively used for chamferless and precision parts mating.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.261-262
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• 2008

Failure Mode Effects and Criticality Analysis (FMECA) evaluates criticality and severity of each failure mode. Generally, those indices are determined subjectively by experts and operators. However, this process has no choice but to include uncertainty. In this paper, a method for eliciting expert opinions considering its uncertainty is proposed to evaluate the criticality and severity. In addition, a fuzzy expert system is constructed to determine the crisp value of risk level for each failure mode. The results are worth considering while deciding the proper policies for each component of the system.