• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2003년도 춘계종합학술대회논문집
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• pp.426-429
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• 2003

본 논문에서는 3차원 물체의 인식을 위한 표면 분류시 그 임계치를 선정하는 방법에 대해 제안하고자 한다. 특히 보다 세밀하고 복잡한 물체의 표현을 위해 사용하여 왔던 평균 곡률과 가우스곡률이 가지고 있던 문제점인 임계치 선정 문제를 통계적 방법에 의해 해결하는 방법을 제안하고자 한다. 끝으로 본 논문의 유용성을 실험에 의해 입증하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.313-316
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• 2004

Model selection is the process that sets up the regularization parameter in the support vector machine or regularization network by using the external methods such as general cross validation or L-curve criterion. This paper suggests that the regularization parameter can be obtained simultaneously within the learning process of neural networks without resort to separate selection methods. In this paper, extended kernel method is introduced. The relationship between regularization parameter and the bias term in the extended kernel is established. Experimental results show the effectiveness of the new model selection method.

• 한국건축시공학회지
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• 제2권1호
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• pp.147-154
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• 2002

In the Past, The selection of individual method of construction was done by head of construction site or an experienced person very frequently. By doing this, The wrong selection of construction method without exact adjudication of construction site situation lead to increasing of cost and extension of construction term. Finally it will effect all over the construction process. Especially, In case of underground construction in the beginning, there are a lot of a variable factor and it also effect on the entire construction process and it need very careful process. The purpose of this study is to present the best suitable methodology for selection of construction method by considering potential risk of construction method and variables together with external condition for underground construction. The purpose of this study Is to select the most suitable construction method by analysing potential conditions(construction site situation and client request in designing ) To do this, We prepared arrangement rule to arrange the conditions for construction method. And thin make checklist of the analyzing construction method. Though above process, To expect the risk of individual construction method using above risk checklist and using Analytic Hierarchy process among Multiple-Criteria Decision making, the professional opinions is to be adapted. By doing this, it can lead and select the most suitable construction method considering the data which get from risk density test.

• 대한기계학회논문집
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• 제14권5호
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• pp.1079-1086
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• 1990

본 연구에서는 모아레 경사격자법(moire tilted master grating method)을 개 발하여 그 유용성을 확인하고 이를 굴절 및 편심균열의 응력확대계수의 해석에 확대 적용하여 다점선정법의 적용범위를 넓히고, 또 분포균열 및 임의 형균열의 해석 가능 성을 타진하여 완성된 실험법으로서의 위치를 구축하는데 목적이 있다.

• Journal of the Korean Data and Information Science Society
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• 제27권6호
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• pp.1653-1660
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• 2016

Smoothly clipped absolute deviation (SCAD) penalty is known to satisfy the desirable properties for penalty functions like as unbiasedness, sparsity and continuity. In this paper, we deal with the regression function estimation and variable selection based on SCAD penalized censored regression model. We use the local linear approximation and the iteratively reweighted least squares algorithm to solve SCAD penalized log likelihood function. The proposed method provides an efficient method for variable selection and regression function estimation. The generalized cross validation function is presented for the model selection. Applications of the proposed method are illustrated through the simulated and a real example.

• 제어로봇시스템학회논문지
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• 제19권12호
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• pp.1081-1088
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• 2013

Hyperspectral cameras acquire reflectance values at many different wavelength bands. Dimensions tend to increase because spectral information is stored in each pixel. Several attempts have been made to reduce dimensional problems such as the feature selection using Adaboost and dimension reduction using the Simulated Annealing technique. We propose a novel material detection method that consists of four steps: feature band selection, feature extraction, SVM (Support Vector Machine) learning, and target and specific region detection. It is a combination of the band ratio method and Simulated Annealing algorithm based on detection rate. The experimental results validate the effectiveness of the proposed feature selection and band ratio method.

• 대한안전경영과학회지
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• 제9권2호
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• pp.195-214
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• 2007

The purpose of this study is to explore the applicability of AHP(Analytic Hierarchy Process) to select more productive projects among various proposed projects in a particular company. To achieve this research objective, the characteristics of project evaluation and selection are first reviewed with respect to when, where, and how the decision is made. Then the theoretical basis of the AHP is briefly reviewed along with its mathematical underpinnings to construct the framework of project evaluation and selection. To be more specific, the evaluation and selection criteria were reorganized in the AHP-based framework to make the process of project evaluation and selection more productive. Project evaluation and selection is one of the most important activities for the most companies to be more advantageous in the market. Despite the importance of decision making process of project selection, not many of how to choose the best project were suggested as the reliable project selection methods in the industries. It may be because it involves various activities related to conflict resolution among different evaluation criteria, high uncertainties of market, and the unclear tradeoff among various project objectives. Furthermore, the decision, once made at this point, tends to be irrevocable until the whole process turns out to be a complete success or failure. As the result, the AHP method showed better financial performance rather than the traditional method in a case study.

• 스마트미디어저널
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• 제12권3호
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• pp.30-37
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• 2023

Alzheimer's disease (AD) symptoms are being treated by early diagnosis, where we can only slow the symptoms and research is still undergoing. In consideration, using T1-weighted images several classification models are proposed in Machine learning to identify AD. In this paper, we consider the improvised feature selection, to reduce the complexity by using wrapping techniques and Restricted Boltzmann Machine (RBM). This present work used the subcortical and cortical features of 278 subjects from the ADNI dataset to identify AD and sMRI. Multi-class classification is used for the experiment i.e., AD, EMCI, LMCI, HC. The proposed feature selection consists of Forward feature selection, Backward feature selection, and Combined PCA & RBM. Forward and backward feature selection methods use an iterative method starting being no features in the forward feature selection and backward feature selection with all features included in the technique. PCA is used to reduce the dimensions and RBM is used to select the best feature without interpreting the features. We have compared the three models with PCA to analysis. The following experiment shows that combined PCA &RBM, and backward feature selection give the best accuracy with respective classification model RF i.e., 88.65, 88.56% respectively.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2001년도 학술논문발표회
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• pp.99-117
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• 2001

In the past, The selection of individual method of construction was done by head of construction site or an experienced person very frequently. By doing this, The wrong selection of construction method without exact adjudication of construction site situation lead to increasing of cost and extension of construction term. Finally it will effect all over the construction process. Especially, In case of Underground construction in the beginning, there are a lot of a variable factor and it also effect on the entire construction process and it need rely careful process. The purpose of this study is to present the best suitable methodology fer selection of construction method by considering potential risk of construction method and variables together with external condition for Underground construction. The purpose of this study is to select the most suitable construction method by analysing potential conditions(Construction site situation and Client. Request in designing) To do this, We prepared arrangement rule to arrangement conditions for construction method. And then make Checklist the analyzing construction method. Though above process, To expect the risk of individual construction method using above risk checklist and using Analytic Hierarchy Process among Multiple-Criteria Decision Making, the professional opinions is to be adapted. By doing this, It can lead and select the most suitable considering method considering the data which get from risk density test.

• Journal of Power Electronics
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• 제17권5호
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• pp.1203-1210
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• 2017

This paper presents an improved switching selection method for the direct torque control (DTC) of five-phase induction motors (IMs). The proposed method is conducted using optimal switching selection. A five-phase inverter has 32 voltage vectors which are divided into 30 nonzero voltage vectors and two zero voltage vectors. The magnitudes of the voltage vectors consist of large, medium, and small voltage vectors. In addition, these vectors are related to the torque response and torque ripple. When a large voltage vector is selected in a drive system, the torque response time decreases with an increased torque ripple. On the other hand, when a small voltage vector is selected, the torque response time and torque ripple increase. As a result, this paper proposes an optimal voltage vector selection method for improved DTC of a five-phase induction machine depending on the situation. Simulation and experimental results verify the effectiveness of the proposed control algorithm.