• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2006년도 정기학술발표대회 논문집
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• pp.448-452
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• 2006

리모델링은 기존 건물을 폐기하지 않고 재활용 함으로써 자원의 재활용이라는 측면과 신축과 같은 부가가치를 창출한다는 측면에서 매우 중요하다고 할 수 있다. 그리고 공사에 적절한 공법 선정은 공사비와 공사기간을 줄여주고 품질을 향상시키는 역할을 한다. 또한 리모델링 공사의 경우 현장의 특성과 구조체의 특성이 공사시에 큰 영향을 끼치기 때문에 기존 신축공사 보다 공법선정이 매우 중요하다고 할 수 있다. 그러나 현재의 공법 선정은 시공정보를 반영하지 않고 단지 기존에 주로 사용하던 공법만을 선정하고 있다. 그렇기 때문에 본 연구에서는 공법 선정시 의사결정을 도와주기 위한 tool의 구축 방안을 제안한다.

• 한국컴퓨터정보학회논문지
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• 제27권5호
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• pp.77-84
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• 2022

본 논문에서는 새로운 비지도 특징 선별 기법을 제안한다. 기존 비지도 방식의 특징 선별 기법들은 특징을 선별하기 위해 가상의 레이블 데이터를 정하고 주어진 데이터를 이 레이블 데이터에 사영하는 회귀 분석 방식으로 특징을 선별하였다. 하지만 가상의 레이블은 데이터로부터 생성되기 때문에 사영된 공간이 비슷하게 형성될 수 있다. 따라서 기존의 방법들에서는 제한된 공간에서만 특징이 선택될 수 있었다. 이를 해소하기 위해 본 논문에서는 직교 사영과 저랭크 근사를 이용하여 특징을 선별한다. 이 문제를 해소하기 위해 가상의 레이블을 직교 사영하고 이 공간에 데이터를 사영할 수 있도록 한다. 이를 통해 더 주요한 특징 선별을 기대할 수 있다. 그리고 사영을 위한 변환 행렬에 저랭크 제한을 두어 더 효과적으로 저차원 공간의 특징을 선별할 수 있도록 한다. 이 목표를 달성하기 위해 본 논문에서는 비용 함수를 설계하고 효율적인 최적화 방법을 제안한다. 여섯 개의 데이터에 대한 실험 결과는 제안된 방법이 대부분의 경우 기존의 비지도 특징 선별 기법보다 좋은 성능을 보여주었다.

• International Journal of Control, Automation, and Systems
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• 제3권2호
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• pp.236-243
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• 2005

This paper presents a new stochastic approach for solving combinatorial optimization problems by using a new selection method, i.e. SA-selection, in genetic algorithm (GA). This approach combines GA with simulated annealing (SA) to improve the performance of GA. GA and SA have complementary strengths and weaknesses. While GA explores the search space by means of population of search points, it suffers from poor convergence properties. SA, by contrast, has good convergence properties, but it cannot explore the search space by means of population. However, SA does employ a completely local selection strategy where the current candidate and the new modification are evaluated and compared. To verify the effectiveness of the proposed method, the optimization of a fuzzy controller for balancing an inverted pendulum on a cart is considered.

• Communications for Statistical Applications and Methods
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• 제26권6호
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• pp.575-582
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• 2019

The problem of selecting variables in the presence of outliers is considered. Variable selection and outlier detection are not separable problems because each observation affects the fitted regression equation differently and has a different influence on each variable. We suggest a simultaneous method for variable selection and outlier detection in a linear regression model. The suggested procedure uses a sequential method to detect outliers and uses all possible subset regressions for model selections. A simplified version of the procedure is also proposed to reduce the computational burden. The procedures are compared to other variable selection methods using real data sets known to contain outliers. Examples show that the proposed procedures are effective and superior to robust algorithms in selecting the best model.

• Communications for Statistical Applications and Methods
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• 제22권1호
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• pp.41-54
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• 2015

In this article, we propose nonconcave penalties on a reduced-rank regression model to select variables and estimate coefficients simultaneously. We apply HARD (hard thresholding) and SCAD (smoothly clipped absolute deviation) symmetric penalty functions with singularities at the origin, and bounded by a constant to reduce bias. In our simulation study and real data analysis, the new method is compared with an existing variable selection method using $L_1$ penalty that exhibits competitive performance in prediction and variable selection. Instead of using only one type of penalty function, we use two or three penalty functions simultaneously and take advantages of various types of penalty functions together to select relevant predictors and estimation to improve the overall performance of model fitting.

• 한국CDE학회논문집
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• 제4권2호
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• pp.100-109
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• 1999

The bearing design includes the steps of selection bering type, selection bearing subtype, and determining the peripheral equipments. In this paper decision making methodologies are compared to propose a stepwise decision methodology to the bearing selection problem. An artificial neural network trained with design cases is used for selecting a bearing type in the first step. Then the subtype of the bearing is selected using the weighting method, high is a kind of multi-criteria decision making method. Finally, the types of peripheral equipments such as lubrication devices, seals and bearing housings are determined using a rule-based expert system.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.951-959
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• 2011

The proposed method is based on a penalized censored regression model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log likelihood function of censored regression model. It provide the efficient computation of regression parameters including variable selection and leads to the generalized cross validation function for the model selection. Numerical results are then presented to indicate the performance of the proposed method.

• 융합보안논문지
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• 제6권3호
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• pp.87-95
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• 2006

침입은 컴퓨터 자원의 무결성, 기밀성, 유효성을 저해하고 컴퓨터 시스템의 보안정책을 파괴하는 일련의 행위의 집합이다. 이러한 침입을 탐지하는 침입탐지시스템은 데이터 수집, 데이터의 가공 및 축약, 침입 분석 및 탐지 그리고 보고 및 대응의 4 단계로 구성되어진다. 침입탐지시스템의 방대한 데이터가 수집된 후, 침입을 효율적으로 탐지하기 위해서는 특징 선택이 중요하다. 이 논문에서 유전자 알고리즘과 결정트리를 활용한 특징 선택 방법을 제안한다. 또한 KDD 데이터에서 실험을 통해 방법의 유효성을 검증한다.

• 한국유기농업학회지
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• 제28권2호
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• pp.189-208
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• 2020

The purpose of this study aims to estimate consumption selection attribute, part-worth of organic instant rice through the use of conjoint analysis method. The conjoint analysis is to trace the development of consumer preference among multi-attribute alternatives. The selection attribute was including 4 factors preferred Type of rice, Capacity, Brand and payment price. For this research, a total of 192 questionnaires was collected of which 200 were completed. The research design was a full profile method by orthogonal design then 9 main profiles, 3 holdout sets were created. The results of this research were as follows. Consumers of organic instant rice are consider their importance of selection attributes was in order to price (25.87%), Type of rice (27.231%), Brand/Purchase channel (24.013%) and Capacity (18.494%). The findings of this study have identified 3 clusters for each experience visitors. Each cluster has a different and showed the relative importance or preference values for each accessible attribute of the segmentation.

• 한국컴퓨터정보학회논문지
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• 제20권9호
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• pp.11-20
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• 2015

In order to prevent the elderly people from committing suicide attempts, it is necessary to verify attributes that affect the suicide attempts. It is noted that previous studies have focused on qualitative approaches, and simple correlation analyses to determine the attributes related to the suicide attempts in the elderly people. However, such previous approaches had led to insufficient performance when facing with complicated data sets. In this sense, this study suggests an alternative method in which attribute selection techniques are adopted to determine more relevant attributes of the suicide attempts occurring in Korean elderly people. To verify empirical validity of our proposed method, we used Korea National Health and Nutrition Examination Survey (KNHANES) from January 2007 to December 2012. Empirical results proved that the proposed attribute selection techniques showed better predictive effectiveness; 94.4% compared to the simple statistical methods. This study proposes a way to determining the elderly suicide and preventing it to happen.