• Proceedings of the Korea Port Economic Association Conference
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• 2003.07a
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• pp.253-269
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• 2003

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.79-83
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• 1997

This paper considers the problem of estimating the model parameters and reliability functions for Freund bivariate exponential distribution. Uniformly minimum variance unbiased estimators for model parameters, joint reliability and marginal reliability functions are obtained in the both case of non-identically distributed marginals and identically distributed marginals.

• Korean Journal of Environmental Agriculture
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• v.33 no.4
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• pp.271-281
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• 2014

BACKGROUND: Application of the transfer functions derived from local soil data is necessary in order to develop proper management protocols for agricultural soils contaminated with heavy metals through phytoavailability control of the heavy metals. The aim of this study was to derive the transfer functions of Korean agricultural soils affected by the abandoned mining sites and evaluate suitability of the derived transfer functions. METHODS AND RESULTS: 142 agricultural soils affected by the abandoned mining sites were collected and analyzed. Two extraction methods, including 1 M $NH_4NO_3$ extraction and 0.01 M $Ca(NO_3)_2$ extraction were applied to determine phytoavailable metal pools in soils. Multiple stepwise regression of phytoavailable metal pools against the corresponding total metal concentration and soil properties was conducted to derive suitable transfer functions for estimating phytoavailable heavy metal pools. Applicability of the derived transfer functions was examined by calculating NME and NRMSE. CONCLUSION: Soil pH and organic matter were valid variables for derivation of the transfer functions which were applicable for estimating phytoavailable metal concentrations in the soils being contaminated by heavy metals. In addition, it was confirmed that transfer functions need to be developed based on local soil conditions to accurately estimate heavy metal-phytoavailability.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.32-40
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• 2003

In this study, we develop the Genetic Fuzzy System(GFS) to estimate the link traveling speed. Based on the genetic algorithm, we can get the fuzzy rules and membership functions that reflect more accurate correlation between traffic data and speed. From the fact that there exist missing links that lack traffic data, we added a Case Base Reasoning(CBR) to GFS to support estimating the speed of missing links. The case base stores the fuzzy rules and membership functions as its instances. As cases are accumulated, the case base comes to offer appropriate cases to missing links. Experiments show that the proposed GFS provides the more accurate estimation of link traveling speed than existing methods.

• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.89-99
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• 2006

This article deals with the problem of estimating parameters of Burr Type XII distribution, on the basis of a general progressive Type II censored sample using Bayesian viewpoints. The maximum likelihood estimator does not admit closed form but explicit sharp lower and upper bounds are provided. Assuming squared error loss and linex loss functions, Bayes estimators of the parameter k, the reliability function, and the failure rate function are obtained in closed form. Finally, a simulation study is also included.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.127-145
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• 2009

A novel approach is proposed to effectively estimate the quantile functions of normalized performance indices of reliability constraints in a reliability-based optimization (RBO) problem. These quantile functions are not only estimated as functions of exceedance probabilities but also as functions of the design variables of the target RBO problem. Once these quantile functions are obtained, all reliability constraints in the target RBO problem can be transformed into non-probabilistic ordinary ones, and the RBO problem can be solved as if it is an ordinary optimization problem. Two numerical examples are investigated to verify the proposed novel approach. The results show that the approach may be capable of finding approximate solutions that are close to the actual solution of the target RBO problem.

• Wind and Structures
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• v.13 no.3
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• pp.293-307
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• 2010

This paper describes a new method for the estimation of six complex aerodynamic admittance functions. The aerodynamic admittance functions relate buffeting forces to the incoming wind turbulent components, of which the estimation accuracy affects the prediction accuracy of the buffeting response of long-span bridges. There should be two aerodynamic admittance functions corresponding to the longitudinal and vertical turbulent components, respectively, for each gust buffeting force. Therefore, there are six aerodynamic admittance functions in all for the three buffeting forces. Sears function is a complex theoretical expression for the aerodynamic admittance function for a thin airfoil. Similarly, the aerodynamic admittance functions for a bridge deck should also be complex functions. This paper presents a separated frequency-by-frequency method for estimating the six complex aerodynamic admittance functions. A new experimental methodology using an active turbulence generator is developed to measure simultaneously all the six complex aerodynamic admittance functions. Wind tunnel tests of a thin plate model and a streamlined bridge section model are conducted in turbulent flow. The six complex aerodynamic admittance functions, determined by the developed methodology are compared with the Sears functions and Davenport's formula.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.103-112
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• 2006

Priority-based network service has been widely adopted for the Internet traffic management in the context of IETF differentiated services, and computing optimal prices for such priority-based service is the key topic in many pricing literature. While the equilibrium analysis has been commonly used to this end, many have criticized the validity of the underlying assumption of equilibrium analysis that user utility functions are precisely known. In this paper, we propose a solution for bridging the gap between the existing theoretical work on optimal pricing and the unavailability of precise user utility information in real networks. In the proposed method, the service provider obtains more and more accurate estimates of user utility functions from the initial imprecise knowledge by iteratively changing the price of service levels and observing the users' decisions under the changed price. Our contribution is two-fold. First, we have developed a general principle for estimating the user utility functions. Second, we have developed a novel method for setting the prices that can optimize the extraction of the knowledge about user utility functions. The extensive simulation results demonstrate the effectiveness of our method.

• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.165-175
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• 2002

We consider the problem of estimating the change-point in mean change model with the one change-point. Lombard (1987) suggested change-point estimation based on score functions. Gombay and Huskova (1998) derived a class of change-point estimators with the score function of rank. Various change-point estimators with the log score functions of ranks are suggested and compared via simulation.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.973-981
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• 2010

Quantile regression investigates the quantiles of the conditional distribution of a response variable given a set of covariates. M-quantile regression extends this idea by a "quantile-like" generalization of regression based on influence functions. In this paper we propose a new method of estimating M-quantile regression functions, which uses kernel machine technique. Simulation studies are presented that show the finite sample properties of the proposed M-quantile regression.