• 대한전기학회논문지:전력기술부문A
• /
• 제48권11호
• /
• pp.1394-1400
• /
• 1999

This paper presents and efficient improvement of the iterative eigenvalue calculation method and the selection of initial values in AESOPS algorithm. To determine the initial eigenvalues of the system, system state matrix is constructed with the two-axis generator model. From the submatrices including synchronous and damping coefficients, the initial eigenvalues are calculated by the QR method. Participation factors are also calculated from the above submatrices in order to determine the generators which have a important effect to the specific oscillation mode. Also, the heuristically approximated eigenvalue calculation method in the AESOPS algorithm is transformed to the Newton Raphson Method which is largely used in the nonlinear numerical analysis. The new methods are developed from the AESOPS algorithm and thus only a few calculation steps are added to practice the proposed algorithm.

• 산업경영시스템학회지
• /
• 제35권2호
• /
• pp.163-172
• /
• 2012

In this study, It is assumed that customers are both usage unit of spare parts and stores of displaying and selling the goods that are installation unit of having the spare parts. The demand pattern through the effective order of spare parts and issue list in installation unit is investigated based on the assumption. Current ASL (Authorized Stockage List) selection of the army has been conducted in the way of using the analysis result of real usage experiences on spare parts used during the Korea War. For this study, ASL selection criteria and procedures based on army regulations and field manuals are specified. Since the traditional method does not presents the association analysis on spare parts used for the current equipment operating and does not have the clear criterion and analysis system about the ASL selection, in order to solve these problems, it was carried out that the association rule is employed for analyzing relationship between the effective order and issue list of the spare parts in point of the spare parts between usage unit and occurring month about purchase spare parts based on the star-schema table. Finally the new ASL selection way using the analysis result is proposed.

• 한국지능시스템학회논문지
• /
• 제24권6호
• /
• pp.646-650
• /
• 2014

본 논문에서는 다차원 문제로 인하여 발생하는 패턴 분류 성능의 저하를 방지 하여 퍼지 패턴 분류기의 성능을 개선하기 위하여 다수의 Feature들 중에서 패턴 분류 성능 향상에 기여하는 Feature를 선택하기 위한 새로운 Feature Selection 방법을 제안 한다. 새로운 Feature Selection 방법은 각각의 Feature 들을 퍼지 클러스터링 기법을 이용하여 클러스터링 한 후 각 클러스터가 임의의 class에 속하는 정도를 계산하고 얻어진 값을 이용하여 해당 feature 가 fuzzy pattern classifier에 적용될 경우 패턴 분류 성능 개선 가능성을 평가한다. 평가된 성능 개선 가능성을 기반으로 이미 정해진 개수만큼의 Feature를 선택하는 Feature Selection을 수행한다. 본 논문에서는 제안된 방법의 성능을 평가, 비교하기 위하여 다수의 머신 러닝 데이터 집합에 적용한다.

• Journal of Information Processing Systems
• /
• 제9권1호
• /
• pp.31-40
• /
• 2013

In this paper, a novel method is proposed to build an ensemble of classifiers by using a feature selection schema. The feature selection schema identifies the best feature sets that affect the arrhythmia classification. Firstly, a number of feature subsets are extracted by applying the feature selection schema to the original dataset. Then classification models are built by using the each feature subset. Finally, we combine the classification models by adopting a voting approach to form a classification ensemble. The voting approach in our method involves both classification error rate and feature selection rate to calculate the score of the each classifier in the ensemble. In our method, the feature selection rate depends on the extracting order of the feature subsets. In the experiment, we applied our method to arrhythmia dataset and generated three top disjointed feature sets. We then built three classifiers based on the top-three feature subsets and formed the classifier ensemble by using the voting approach. Our method can improve the classification accuracy in high dimensional dataset. The performance of each classifier and the performance of their ensemble were higher than the performance of the classifier that was based on whole feature space of the dataset. The classification performance was improved and a more stable classification model could be constructed with the proposed approach.

• Journal of the Korean Data and Information Science Society
• /
• 제22권2호
• /
• pp.227-234
• /
• 2011

이 논문에서는 척도화 향상도에 근거한 처방 선택 방법들을 제안하였다. 이 연구는 Park과 Kim(2010)에 의해 사용된 향상도가 특정 범위에 국한되지 않아 얼마나 커야 (혹은 작아야) 큰 (혹은 작은) 값인지 알기 힘든 문제점을 극복하기 위해 제안되었다. 제안된 첫 번째 척도화 향상도는 향상도를 바로 척도화 시켜 0과 1사이의 값을 취하도록 하였으며, 두 번째 척도화 향상도는 향상도-1을 척도화 시켜 -1과 1사의의 값을 취하도록 하였다. 구체적으로 첫 번째 척도화는 향상도를 척도화만 시킨 형태이고, 두 번째 척도화는 향상도를 중심화와 동시에 척도화 시킨 형태이다. 이 척도화 향상도에 근거한 처방 선택 방법들을 응급실 급성 충수염 환자에 적용하여 향상도에 근거한 처방 선택 결과와 비교하였다.

• 지식경영연구
• /
• 제13권3호
• /
• pp.55-77
• /
• 2012

Selecting promising technology is becoming more and more difficult due to the increased number and complexity. In this study, we propose hybrid AHP/DEA-AR method and hybrid AHP/DEA-AR-G method to evaluate efficiency of technology alternatives based on ordinal rating data collected through survey to technology experts in a certain field and select efficient technology alternative as promising technology. The proposed method normalizes rating data and uses AHP to derive weights to improve the credibility of analysis, then in order to avoid basic DEA models' problems, use DEA-AR and DEA-AR-G to evaluate efficiency of technology alternatives. In this study, we applied the proposed methods to clean technology and compared with the basic DEA models. According to the result of the comparison, we can find that the both proposed methods are excellent in confirming most efficient technology, and hybrid AHP/DEA-AR method is much easier to use in the process of technology selection.

• Current Optics and Photonics
• /
• 제8권5호
• /
• pp.472-483
• /
• 2024

This paper presents an intuitive method for selecting an optical material for achromatic and athermal design using the material selection index (MSI). In addition, in the case of a wide wavelength range such as a short-wave infrared (SWIR) waveband, we propose a new material selection method for apochromatic and athermal design by introducing the relative error of partial dispersion (REPD) and a first-order quantity redistribution method. To obtain a suitable material for effective apochromatic design, we first evaluate the REPDs of all lenses, deviated from that of an equivalent lens. Materials with a small REPD are then selected on a glass map to correct residual chromatic aberration while maintaining the existing MSI values to realize athermalization simultaneously. Using this proposed glass selection method, we successfully obtained an apochromatic and athermal telephoto system for SWIR that realizes stable performance over the specified temperature and wide waveband ranges.

• Journal of Advanced Marine Engineering and Technology
• /
• 제40권2호
• /
• pp.138-145
• /
• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• 대한공간정보학회지
• /
• 제5권1호
• /
• pp.27-40
• /
• 1997

최근 항공수요가 급증하고 지방화시대가 도래함에 따라 각 지역마다 지방공항 건설에 박차를 가하고 있다. 그러나 공항의 부적절한 입지는 그 기능발휘에 제한을 초래하게 되고 항공수요의 감소로 이어지게 된다. 따라서 공항의 기능을 최대한으로 발휘할 수 있는 지역대표공항의 건설이 요구되며, 이에 따라 경제적이고 효율적인 공항입지선정 방법이 요망되고 있다. 본 연구는 공항입지선정에 있어서 지형공간정보체계를 활용하여 실제대상지역에 적용한 결과, 지형공간 정보체계가 광범위한 지역을 대상으로 다양한 분석인자를 적용해야 하는 공항입지선정에 있어 효율적이고 과학적인 분석을 위한 새로운 기법임을 제시할 수 있었다. 그리고 공항입지선정 시 요구되는 분석인자들간의 우선순위와 자료의 등급 및 상대적인 경중률을 산정하는 과정에서 쌍체비교방법과 델파이기법을 병행하여 실시함으로서 분석결과의 객관성을 보다 더 향상시킬 수 있었다.

• 경영과학
• /
• 제16권1호
• /
• pp.89-99
• /
• 1999

Combat fatigues are issued to military personnel with ready made clothes. Ready made combat fatigues should be fitted to various bodies of military personnel within given standard size. This paper develops a standard sizes selection method in order to increase the coverage rate and fitness for combat fatigues. The method utilizes a generalized learning vector quantization(GLVQ) algorithm that is one of cluster algorithm in neural networks techniques. The GLVQ moves the standard sizes from initial arbitrary sizes to next sizes in order to increase more coverage rate and fitness. Finally, when it cannot increase those, algorithm is terminated. The results of this method show more coverage rate and fitness than those of the other methods.