• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.433-439
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• 1998

In this paper, we present an approach to the structure identification based on the input space partition methods and to the parameter identification by hybrid learning method in neuro-fuzzy system. The structure identification can automatically estimate the number of membership function and fuzzy rule using grid partition, tree partition, scatter partition from numerical input-output data. And then the parameter identification is carried out by the hybrid learning scheme using back-propagation and least squares estimate. Finally, we sill show its usefulness for neuro-fuzzy modeling to truck backer-upper control.

• Journal of the Korean Institute of Navigation
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• v.12 no.3
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• pp.23-37
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• 1988

This paper deals with the method of determining the drag of hull surface which has any quality of roughness. The method consists mainly of the theoretical point of view, then the theory enables the drag coefficient to be calculated at full scale. The hydrodynamical roughness function of hull surface ${\triangle}U_+$, affected by the hull roughness are considered as to two cases, smooth surface and rough surface case separately. The inadequacy of a single parameter to define hull roughness is discussed and thus an as additional texture parameter is proposed.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.213-224
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• 2014

In this paper, we study the problem of transforming to normality. We propose to estimate the transformation parameter by minimizing a weighted squared distance between the empirical characteristic function of transformed data and the characteristic function of the normal distribution. Our approach also allows for other symmetric target characteristic functions. Asymptotics are established for a random sample selected from an unknown distribution. The proofs show that the weight function $t^{-2}$ needs to be modified to have thinner tails. We also propose the method to compute the influence function for M-equation taking the form of U-statistics. The influence function calculations and a small Monte Carlo simulation show that our estimates are less sensitive to a few outliers than the maximum likelihood estimates.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.383-388
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• 2009

In this paper we propose a variance function estimation method based on kernel trick for replicated data or data consisted of sample variances. Newton-Raphson method is used to obtain associated parameter vector. Furthermore, the generalized approximate cross validation function is introduced to select the hyper-parameters which affect the performance of the proposed variance function estimation method. Experimental results are then presented which illustrate the performance of the proposed procedure.

• Environmental and Resource Economics Review
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• v.11 no.4
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• pp.689-706
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• 2002

This paper makes some contributions on optimal environmental taxes in the generalized utilitarian social welfare function. It is not to suggest as to appropriate environmental tax rates but to contribute the direction of environmental tax policy. The tax rates depend on parameters of individual utility function (CES utility function) and social welfare function and income tax rate. The major findings are that, as the elasticity of substitution between labor and leisure and the concavity of social welfare function increase, both the optimal tax rates and the government demogrants rise. And, as the parameter of environmental pollution in the individual utility function increases, the optimal tax rates also increase. For the future study, this model involves the income tax and the capital tax as endogenous variables and the wage changes due to international trade.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.95-104
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• 2010

The storage function model is one of the most commonly used models for flood forecasting and warning system in Korea. This paper studies the physical significance of the storage function model by comparing it with kinematic wave model. The results showed universal applicability of the storage function model to Korean basins. Through a comparison of the basic equations for the models, the storage function model parameters, K, P and $T_l$, are shown to be related with the kinematic wave model parameters, k and p. The analysis showed that P and p are identical and K and $T_l$ can be related to k, basin area, and coefficients of Hack's law. To apply the storage function model throughout the southern part of Korean peninsular, regional parameter relationships for K and $T_l$ were developed for watershed area using data from 17 watersheds and 101 flood events. These relationships combine the kinematic wave parameters with topographic information using Hack's Law.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.745-746
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• 2012

• 대한핵의학회:학술대회논문집
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• 1973.11a
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• pp.51.3-52
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• 1973

• Journal of the Korean Mathematical Society
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• v.36 no.4
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• pp.679-679
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• 1999

• Proceedings of the Korea Water Resources Association Conference
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• 1984.07a
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• pp.115-117
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• 1984