• Journal of KIISE:Databases
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• v.28 no.4
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• pp.545-557
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• 2001

In this paper we propose a hierarchical classification algorithm based on rough membership function which can reason a new object approximately. We use the fuzzy reasoning method that substitutes fuzzy membership value for linguistic uncertainty and reason approximately based on the composition of membership values of conditional sttributes Here we use the rough membership function instead of the fuzzy membership function It can reduce the process that the fuzzy algorithm using fuzzy membership function produces fuzzy rules In addition, we transform the information system to the understandable minimal decision information system In order to do we, study the discretization of continuous valued attributes and propose the discretization algorithm based on the rough membership function and the entropy of the information theory The test shows a good partition that produce the smaller decision system We experimented the IRIS data etc. using our proposed algorithm The experimental results with IRIS data shows 96%~98% rate of classification.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.323-340
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• 1997

In this study we prove the mesh-independence principle via Steffensen's method. This principle asserts that when Steffensen's method is applied to a nonlinear equation between some Banach spaces as well as to some finite-dimensional discretization of that equation then the behavior of th discretized process is asymptoti-cally the same as that for the original iteration. Local and semilo-cal convergencve results as well as an error analysis for Steffensen's method are also provided.

• Structural Engineering and Mechanics
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• v.8 no.5
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• pp.439-452
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• 1999

A simple numerical scheme suitable for tracing the fracture propagation path for structures idealized by means of Hillerborg's classical cohesive crack model is presented. A direct collocation, multidomain boundary element method is adopted for the required space discretization. The algorithm proposed is necessarily iterative in nature since the crack itinerary is a priori unknown. The fracture process is assumed to be governed by a path-dependent generally nonlinear softening law. The potentialities of the method are illustrated through two examples.

• Journal of the Korean Mathematical Society
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• v.54 no.1
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• pp.193-213
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• 2017

We investigate an efficient approximation of solution to stochastic Burgers equation driven by an additive space-time noise. We discuss existence and uniqueness of a solution through the Orstein-Uhlenbeck (OU) process. To approximate the OU process, we introduce the Karhunen-$Lo{\grave{e}}ve$ expansion, and sparse grid stochastic collocation method. About spatial discretization of Burgers equation, two separate finite element approximations are presented: the conventional Galerkin method and Galerkin-conservation method. Numerical experiments are provided to demonstrate the efficacy of schemes mentioned above.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.75-86
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• 2022

This study aims to solve the problem of class imbalance in numerical data by using a deep learning-based Variational AutoEncoder and to improve the performance of the learning model by augmenting the learning data. We propose 'D-VAE' to artificially increase the number of records for a given table data. The main features of the proposed technique go through discretization and feature selection in the preprocessing process to optimize the data. In the discretization process, K-means are applied and grouped, and then converted into one-hot vectors by one-hot encoding technique. Subsequently, for memory efficiency, sample data are generated with Variational AutoEncoder using only features that help predict with RFECV among feature selection techniques. To verify the performance of the proposed model, we demonstrate its validity by conducting experiments by data augmentation ratio.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2029-2032
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• 2004

The quantity of data were rapidly increased recently and caused the data overwhelming. This led to be difficult in searching the required data. The method of eliminating redundant data was needed. One of the efficient methods was Knowledge Discovery in Database (KDD). Generally data can be separate into 2 cases, continuous data and discrete data. This paper describes algorithm that transforms continuous attributes into discrete ones. We present an Improved Class Attribute Interdependence Maximization (ICAIM), which designed to work with supervised data, for discretized process. The algorithm does not require user to predefine the number of intervals. ICAIM improved CAIM by using significant test to determine which interval should be merged to one interval. Our goal is to generate a minimal number of discrete intervals and improve accuracy for classified class. We used iris plant dataset (IRIS) to test this algorithm compare with CAIM algorithm.

• Journal of Powder Materials
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• v.22 no.5
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• pp.337-343
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• 2015

Powder compaction is a continually and rapidly evolving technology where it is a highly developed method of manufacturing reliable components. To understand existing mechanisms for compaction, parameter investigation is required. Experimental investigations on powder compaction process, followed by numerical modeling of compaction are presented in this paper. The experimental work explores compression characteristics of soft and hard ductile powder materials. In order to account for deformation, fracture and movement of the particles, a discrete-finite element analysis model is defined to reflect the experimental data and to enable investigations on mechanisms present at the particle level. Effects of important simulation factors and process parameters, such as particle count, time step, particle discretization, and particle size on the powder compaction procedure have been explored.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.4
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• pp.50-58
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• 1994

To examine the residual stress field resulting from stamping process for the lower control arm of a car, the explicit finite element analysis is performed for the stamping process by way of the ABAQUS Explicit. The residual stress is obtained in terms of the Von Mises stress and other parameters such as equivalent plastic strain, the change of blank thickness, the final configuration of the blank and the spring back effect are also considered. Moreover, discussed is the convergence of the explicit FEM versus the punch sped and the element discretization

• Coupled systems mechanics
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• v.4 no.3
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• pp.211-235
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• 2015

In this work we present a one-dimensional damage model capable of representing the dynamic fracture for elastodamage bar with combined hardening in fracture process zone - FPZ and softening with embedded strong discontinuities. This model is compared with another one we recently introduced (Do et al. 2015) and it shows a good agreement between two models. Namely, it is indicated that strain-softening leads to a sensitivity of results on the mesh discretization. Strain tends to localization in a single element which is the smallest possible area in the finite element simulations. The strain-softening element in the middle of the bar undergoes intense deformation. Strain increases with increasing mesh refinement. Strain in elements outside the strain-softening element gradually decreases to zero.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.282-288
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• 1988

A Multi-grid method is introduced to Finite Element Analysis of electromagnetic field problems in order to reduce the computational time. The puropse of this work is to study how to intermix discretization and solving process, thereby making the process more effective and to find the optimal factors of Multi-grid method. Several numerical experiments with linear models of uniform and nonuniform grids confirm that the proposed algorithm can reduce the computational time very effectively as compared with con ventional iterative methods. The best results are obtained with V cycle and S.O.R. with the acce leration factor of 1.3-1.4 for smoothing.